Google on Monday disclosed that it identified an unknown threat actor using a zero-day exploit that it said was likely developed with an artificial intelligence (AI) system, marking the first time the technology has been put to use in the wild in a malicious context for vulnerability discovery and exploit generation. The activity is said to be the work of cybercrime threat actors who appear to
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A malicious Hugging Face repository managed to take a spot in the platform's trending list by impersonating OpenAI's Privacy Filter open-weight model to deliver a Rust-based information stealer to Windows users. The project, named Open-OSS/privacy-filter, masqueraded as its legitimate counterpart released by OpenAI late last month (openai/privacy-filter), including copying the entire description
Presently sponsored by: Report URI: Guarding you from rogue JavaScript! Don’t get pwned; get real-time alerts & prevent breaches #SecureYourSite Today, we welcome the 43rd government onboarded to Have I Been Pwned's free gov service, Bangladesh. The BGD e-GOV CIRT department now has full access to query all their government domains via API, and monitor them against future breaches. Bangladesh joins a growing list of national governments using HIBP to help protect their public sector digital assets, and we look forward to supporting their efforts to identify exposure of government email addresses in data breaches and respond quickly when new incidents appear.
Checkmarx warned over the weekend that a rogue version of its Jenkins Application Security Testing (AST) plugin had been published on the Jenkins Marketplace. [...]
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Monday, May 11
I think the bigger point here is that AI has clearly been accelerating attackers, so it makes sense that frontier models are now being packaged more directly for defenders too. Not sure how to start using it yet or get access
California Attorney General Rob Bonta announced a proposed $12.75 million settlement agreement with General Motors (GM) over allegations that the company violated the California Consumer Privacy Act (CCPA). [...]
Presently sponsored by: Report URI: Guarding you from rogue JavaScript! Don’t get pwned; get real-time alerts & prevent breaches #SecureYourSite Today, we welcome the 43rd government onboarded to Have I Been Pwned's free gov service, Bangladesh. The BGD e-GOV CIRT department now has full access to query all their government domains via API, and monitor them against future breaches. Bangladesh joins a growing list of national governments using HIBP to help protect their public sector digital assets, and we look forward to supporting their efforts to identify exposure of government email addresses in data breaches and respond quickly when new incidents appear.
Checkmarx warned over the weekend that a rogue version of its Jenkins Application Security Testing (AST) plugin had been published on the Jenkins Marketplace. [...]
A security researcher has released a proof-of-concept tool named GhostLock that demonstrates how a legitimate Windows file API can be abused in attacks to block access to files stored locally or on SMB network shares. [...]
The International Monetary Fund (IMF) is warning that AI could become a growing threat to global financial stability by making cyberattacks faster and more sophisticated. In a new analysis, the organization describes how new AI tools can help attackers identify and exploit security vulnerabilities in banks, payment systems, and cloud services in record time.
Key Takeaways Sara Pentest and Sara Pentest+ Are Now Generally Available Since releasing Sara Pentest as general availability earlier this month, we’ve also shipped a set of platform updates that make it easier to scope, launch, and act on Sara findings at scale. This post walks through what’s new with the Synack PTaaS platform, and […] The post What’s New with Sara Pentest: Closing the Coverage Gap, One Test at a Time appeared first on Synack .
With the recent Canvas ransomeware attack and articles such as [https://programs.com/resources/small-business-ransomware-stats/](https://programs.com/resources/small-business-ransomware-stats/), you can only think of all the security features these companies and managment said were "just too expensive". What are your non-negotiables that your company does (or should but does not do) that you find to be worth it no matter the price?
A threat actor named Mr_Rot13 has been attributed to the exploitation of a recently disclosed critical cPanel flaw to deploy a backdoor codenamed Filemanager on compromised environments. The attack exploits CVE-2026-41940, a vulnerability impacting cPanel and WebHost Manager (WHM) that could result in an authentication bypass and allow remote attackers to gain elevated control of the control
VU#471747: dnsmasq contains several vulnerabilities, including attacker DNS redirect, privilege escalation, and heap manipulation
Overview dnsmasq is affected by multiple memory safety and input validation vulnerabilities, including heap buffer overflows, heap corruption, and code execution flaws. Collectively, these vulnerabilities enable attackers to poison cached DNS records, bypass security controls, crash the dnsmasq process, or under certain conditions, achieve local privilege escalation. dnsmasq has released version 2.92rel2 to fix the vulnerabilities. Description dnsmasq is an open-source networking tool that provides DNS forwarding, DHCP, and network boot services for small-to-medium sized networks and home routing devices. It can also function as a DNS resolver, which is the primary exploitation use case for several of the vulnerabilities described below, tracked collectively as CVE-2026-2291, CVE-2026-4890, CVE-2026-4891, CVE-2026-4892, CVE-2026-4893, and CVE-2026-5172. CVE-2026-2291 dnsmasq's extract_name() function can be abused to cause a heap buffer overflow, enabling an attacker to inject false DNS cache entries. This could cause DNS queries to be redirected to attacker-controlled IP addresses or result in a Denial of Service (DoS). CVE-2026-4890 An infinite-loop flaw in the DNSSEC validation of dnsmasq allows remote attackers to cause Denial of Service (DoS) conditions via a crafted DNS packet. CVE-2026-4891 A heap-based out-of-bounds read vulnerability in the DNSSEC validation of dnsmasq allows remote attackers to leak memory information via a crafted DNS packet. CVE-2026-4892 A heap-based out-of-bounds write vulnerability in the DHCPv6 implementation of dnsmasq allows local attackers to execute arbitrary code with root pr
Google on Monday disclosed that it identified an unknown threat actor using a zero-day exploit that it said was likely developed with an artificial intelligence (AI) system, marking the first time the technology has been put to use in the wild in a malicious context for vulnerability discovery and exploit generation. The activity is said to be the work of cybercrime threat actors who appear to
Found a CWE-602 in Apple News Publisher — client-side eligibility check, one Burp rule, free iCloud account walks out with full Admin access and a signed EULA. Apple closed it four times as "expected behavior." MITRE disagreed. 116 days in, still open.
Overview Casdoor contains an arbitrary file write vulnerability in the implementation of its "Local File System" storage provider. Due to insufficient sanitization of user-supplied paths, an authenticated user with file upload permissions can escape the intended storage directory and write files elsewhere on the target filesystem. The vulnerability allows attackers to bypass Casdoor’s storage sandbox and perform unauthorized actions with the privileges of the Casdoor runtime user. Description Casdoor is an open-source identity and access management (IAM) platform and Model Context Protocol (MCP) gateway that provides authentication, single sign-on, and multi-protocol identity services for applications. Internally, it uses its Local File System storage provider to save files to a dedicated $CASDOOR/files/ directory. During a file upload via the /api/upload-resource endpoint, the Casdoor application determines the target storage filepath by concatenating the user-supplied parameters pathPrefix and fullFilePath . However, values provided for pathPrefix are not properly sanitized, so directory traversal sequences such as ../../ are accepted without any integrity or permission checks beyond those of the OS user running the Casdoor process. The application does not verify that the destination filepath remains inside the dedicated storage directory, and it will create or overwrite any file that the Casdoor process has permission to modify. CVE-2026-6815 An arbitrary file write vulnerability exists in Casdoor's Local File System storage provider. Due to insufficient path sanitization, an authenticated attacker with file upload privileges can perform a path tra
The EtherRAT malware family was first reported by Sysdig back in December 2025. At that time, the initial access vector was exploitation of CVE-2025-55182 (React2Shell) targeting Linux servers. In March 2026, a Windows variant campaign was reported by Atos, with their investigation showing evidence of activity going back to the previous December. In April, we […] The post Flash Alert: EtherRat and TukTuk C2 End in The Gentleman Ransomware appeared first on The DFIR Report .
Resetting a password doesn't always remove attackers from Active Directory. Specops Software explains how cached credentials and Kerberos tickets can keep attackers authenticated after a reset. [...]
**IOCX v0.7.3 — deterministic PE structural validation for reproducible malware analysis** A recurring issue in malware research is the lack of determinism in PE parsing. Small deviations in malformed headers, inconsistent RVA→file‑offset resolution, truncated sections, or ambiguous directory boundaries often lead different parsers—and even different versions of the \*same\* parser—to produce divergent structural interpretations. This undermines reproducibility, complicates longitudinal tracking of families that exploit PE edge cases, and introduces noise into automated pipelines. IOCX v0.7.3 addresses this by implementing a fully deterministic structural‑validation framework for PE files. The validator stack has been written around explicit, conservative rules governing entrypoint resolution, section‑table integrity, RVA‑graph consistency, TLS callback validation, signature‑directory bounds, and entropy classification. All decisions are derived from strict structural criteria rather than heuristic fallbacks. The result is a parser that produces stable, reproducible outputs across environments, versions, and malformed samples. **Same input → same structural interpretation → same anomaly set.** For researchers working with adversarial PEs, loader‑abuse techniques, or large‑scale corpora where methodological consistency matters, this release may be of interest. IOCX v0.7.3 is available on PyPI: `pip install iocx` [https://pypi.org/project/iocx/](https://pypi.org/project/iocx/) [https://github.com/iocx-dev/iocx](https://github.com/iocx-dev/iocx) **Deterministic by design.**
Rough Monday. Somebody poisoned a trusted download again, somebody else turned cloud servers into public housing, and a few crews are still getting into boxes with bugs that should’ve died years ago — the same old holes, same lazy access paths, same “how the hell is this still open” feeling. One report this week basically reads like a guy tripped over root access by accident and decided to stay
Health service has given US tech firm ‘unlimited access’ to certain data to build integrated platform, according to reports UK politics live – latest updates MPs have warned that an NHS decision to grant Palantir access to identifiable patient information in its plan to use AI to improve the health service is “dangerous” and will fuel public fears that data privacy is not being prioritised. NHS England has allowed staff from the US tech firm and other contractors to access patient data before it has been pseudonymised, despite internal fears of a “risk of loss of public confidence”, the Financial Times reported. Continue reading...
Defending a network at 2 am looks a lot like this: an analyst copy-pasting a hash from a PDF into a SIEM query. A red team script is being rewritten by hand so the blue team can use it. A patch waiting on a change-approval window that's longer than the exploitation window itself. Nobody in that chain is incompetent. Every human is doing their job correctly. The problem is the system, its
Palo Alto PAN-OS has a pre-auth root RCE right now. No patch until May 13. Fourth major security gateway CVE this yea
CVE-2026-0300: unauthenticated buffer overflow in the PAN-OS User-ID Authentication Portal, root code execution, actively exploited. CISA KEV listed. Patch expected May 13. If you are running PAN-OS, restrict management interface access now. We put together a piece on the CVE and the structural argument behind why this category keeps producing these: [https://zeroport.com/blog/pan-os-cve-2026-0300-pre-auth-rce](https://zeroport.com/blog/pan-os-cve-2026-0300-pre-auth-rce)
A new variant of the TrickMo Android banking malware, delivered in campaigns targeting users across Europe, introduces new commands and uses The Open Network (TON) for stealthy command-and-control communications. [...]
I recently published a security research post on the myAudi connected vehicle platform. I found that anyone with a VIN can access a sensitive informations about car and ownership I think the topic is useful beyond Audi itself, because many vendors now rely on these “connected vehicle” platforms and mobile apps, often with very similar architectures and assumptions
A malicious Hugging Face repository managed to take a spot in the platform's trending list by impersonating OpenAI's Privacy Filter open-weight model to deliver a Rust-based information stealer to Windows users. The project, named Open-OSS/privacy-filter, masqueraded as its legitimate counterpart released by OpenAI late last month (openai/privacy-filter), including copying the entire description
To reduce the amount of noise from questions, we have disabled self-posts in favor of a unified questions thread every week. Feel free to ask any question about reverse engineering here. If your question is about how to use a specific tool, or is specific to some particular target, you will have better luck on the [Reverse Engineering StackExchange](http://reverseengineering.stackexchange.com/). See also /r/AskReverseEngineering.
I’m happy to announce that we are releasing the beta version of RAPTR, a fully open source, API driven collaboration platform built specifically for red and purple team engagements. Check out the code on GitHub , read the docs , or try out the latest build at our sandbox . Why I built it Up until recently, our team relied on PurpleOps for our Purple Team engagements . It’s a solid tool and served as a good starting point for us. Eventually, we needed more out of it, so we maintained our own custom f
Sunday, May 10
Presently sponsored by: Report URI: Guarding you from rogue JavaScript! Don’t get pwned; get real-time alerts & prevent breaches #SecureYourSite Well, it's the day before the Instructure "pay or leak" deadline (at least by my Aussie watch), and the company remains removed from the ShinyHunters website. In its place sits a press statement that amounts to "we're not making any statements". So did they pay? And if so, what lofty figure would an incident of this scale command? The lawsuits are already being prepared (search for "instructure class action lawsuit"), so perhaps that will be the catalyst for transparency. What a crazy time.
ShinyHunters cashout fingerprint; on-chain trace of the May 2024 AT&T ransom payment, with persistent laundering-service hubs identified through 2025
ShinyHunters has been one of the most visible financially-motivated cybercrime groups of the past two years, with attacker-claimed campaigns spanning the 2024 Snowflake-tenant breaches (AT&T 109M accounts, Ticketmaster 560M, Santander, Neiman Marcus), the 2025 to 2026 Salesforce-tenant extortion campaign (300 to 400 organisations claimed, including Okta, LastPass, Sony, AMD), and the May 2026 Canvas/Instructure incident (3.65 TB / 275M records claimed across 8,809 schools). Mandiant tracks the broader ecosystem as a family of overlapping UNC clusters (UNC5537, UNC6040, UNC6240, UNC6395). The public ShinyHunters / BreachForums persona spans this family rather than mapping cleanly to any single cluster. Despite this footprint, almost none of these events have public payment data. Most are not even confirmed paid. The one exception is the May 2024 AT&T payment of approximately 5.7 BTC (\~$370K), confirmed by Wired via internal blockchain analytics, with the approximate settlement date known, but the transaction hash itself was never published. AT&T did not file an SEC disclosure either. That single anchor opens a more concrete question: how far can ShinyHunters actually be tracked using only public data? I wrote a paper that works through it end to end. On-chain analysis using BigQuery, Blockstream Esplora, and three free attribution databases. No commercial CTI tooling, no licensed labels. **Pipeline (5 stages):** 1. BigQuery bulk filter on amount and time window, 500 candidates. 2. Recipient profiling via Blockstream Esplora (lifetime tx count, spend shape). 3. Sender-side cluster analysis using common-input ownership; targeting broker-aggregation patterns. 4. Depth-12 concurrent forward trace, top-K=4 fan-out. 5. Terminal attribution via OKLink, BitInfoCharts, WalletExplorer. **Result:** A single highest-fit candidate: 5.71997804 BTC paid 2024-05-17 22:04 UTC to a fresh recipient, spent in 6 minutes, routed through a six-cycle automated peel chain, terminating at exchange deposit clusters at HitBTC and Binance. Funding side carries the broker-aggregation fingerprint expected from an incident-response broker sourcing via OTC desks: 4x 1.147 BTC peels converging in a 90-minute window pre-payout. **CTI-relevant finding (§4.3 to §4.4):** Upstream peel-chain hubs feeding the candidate's consolidations are reused across multiple non-AT&T victim flows of the same laundering service, with continued activity through late 2025, terminating at the same HitBTC and Binance deposit clusters. The infrastructure persists across events. The operator-level fingerprint (single-use or low-use hub addresses, self-iteration, fan-out dispatcher pattern, convergence at fixed exchange terminals) is the durable signal, not any one transaction. The paper closes with the legal pathway from chain endpoint to indictment and a scoped compliance-request template targeting the cashout endpoint. **Asking for:** 1. Technical feedback / methodology critique. 2. arXiv [cs.CR](http://cs.CR) endorsement; please leave a comment if you are able to provide this. [github.com/tr4m0ryp/shinyhunters-gotta-catch-em-all/blob/main/Gotta\_Catch\_Em\_All\_ShinyHunters.pdf](http://github.com/tr4m0ryp/shinyhunters-gotta-catch-em-all/blob/main/Gotta_Catch_Em_All_ShinyHunters.pdf) Tooling and dataset released for reuse against future ShinyHunters events with a publicly disclosed amount and window.
I am proud to announce the release of **Crow-Eye v0.10.0**. This milestone marks the official launch of **The Eye** a robust intelligence layer designed to integrate your own AI agents directly into **Crow-Eye,** This isn't just a regular update; it’s a massive milestone for us . My goal from day one has been to build an ecosystem that doesn't just chase known signatures, but actually gives investigators the power to hunt zero-days But as we celebrate this release and introduce our new AI layer, we need to talk about the elephant in the room. # The Problem with AI in Forensics There’s a huge rush right now to slap AI onto cybersecurity tools, and honestly, a lot of it is dangerous. We are seeing "black box" solutions where investigators feed raw data into an LLM and just trust the answers it spits out. In DFIR, an AI hallucination can ruin a case. An answer without mathematical, binary proof is worthless. If an AI agent cannot anchor its reasoning to exact offsets, hashes, and unmanipulated timestamps, we cannot trust it. To fix this, I realized we had to architect a system where the AI is bound by the exact same strict evidentiary rules as a human analyst. # The Starting Line: Automated Triage Before the AI even wakes up, Crow-Eye does the heavy lifting. When you launch **The Eye**, the platform immediately runs a high-speed Automated Triage phase. It queries the underlying SQLite databases to map out the ground truth: active users, execution histories, accessed files, USB devices, and Auto Run configs. This builds a comprehensive **Initial Report**. This report isn't the final investigation it’s the baseline. It’s the verified starting line before we let the AI touch the data. # The Brain of "The Eye" I believe you should have total control over your data and your analytical "brain." That’s why The Eye is completely modular. You can plug in whatever intelligence fits your environment: * **Cloud AI Models:** Hook up your public API keys for high-performance reasoning. * **Offline Servers & Local Inference:** For air-gapped labs where privacy is non-negotiable. * *Dev Note:* A lot of my testing and development for The Eye was actually done using **LM Studio** and Google’s open-weights models (like the **Gemma** family). If you're a solo investigator, running Gemma locally on your own machine is incredibly powerful. Just a tip: push your context window as high as possible to handle the dense forensic payloads! * **CLI Agents:** If you are a developer or researcher, you can hook up your own custom-built local agents, or seamlessly pipe in tools like **Claude Code** and the **Gemini CLI**. https://preview.redd.it/zdg32192ic0h1.png?width=2023&format=png&auto=webp&s=a1458500b3765ccb1a7fb4018a9dcd2203bd7a1a # Keeping the AI Honest: The Ghassan Elsman Protocol (GEP) Triage gives us the data, but the **Ghassan Elsman Protocol (GEP)** ensures the AI doesn't mess it up. The GEP is a strict set of rules hardcoded into the workflow to maintain a perfect chain of custody: 1. **Case Awareness:** The Initial Report is injected directly into the prompt to ground the AI in reality. 2. **Pre-Flight Ping:** Validates backend connectivity to stop silent failures. 3. **Evidence Anchoring:** Automatically tags and preserves raw hashes, IPs, and timestamps in the chat history. 4. **Chain of Custody:** Every truncation or data preservation event is meticulously logged. 5. **Non-Repudiation:** Messages are assigned deterministic, hash-linked IDs so records can't be altered. 6. **Context Pinning:** Critical evidence is locked and excluded from automated AI summarization. 7. **Tool Traceability:** Every tool the AI uses (like querying LOLBAS) is logged with exact execution counts. 8. **Machine-Readable Synthesis:** You get a clean JSON audit trail at the end to prove compliance. # What's Next: Bridging Analysis and Anatomy While The Eye handles the high-speed analysis, our educational hub, **Eye Describe**, In upcoming updates, we are going to start building a bridge between these two tools. The goal is to gradually integrate visual references alongside the AI's findings. We want to reach a point where the AI doesn't just give you an answer, but helps point you toward the structural anatomy of the artifact it analyzed. It’s an iterative, ongoing project, but we believe it is an important step toward total forensic transparency. This is the very first release of The Eye. You might hit a few bumps connecting to certain local backends or managing specific CLI tools, but we are actively squashing bugs and refining the experience over the next few weeks. Please submit any issues you find! The latest source code and release are available right now on our GitHub. For those waiting for the compiled `.exe` version, it will be dropping very soon on our official website. **GitHub :** [https://github.com/Ghassan-elsman/Crow-Eye](https://github.com/Ghassan-elsman/Crow-Eye) **good hunting**
German authorities have shut down a relaunch version of the criminal marketplace 'Crimenetwork' that generated more than 3.6 million euros, and arrested its operator. [...]
Cybersecurity researchers have disclosed a critical security vulnerability in Ollama that, if successfully exploited, could allow a remote, unauthenticated attacker to leak its entire process memory. The out-of-bounds read flaw, which likely impacts over 300,000 servers globally, is tracked as CVE-2026-7482 (CVSS score: 9.1). It has been codenamed Bleeding Llama by Cyera. Ollama is a
The compression of the exploit timeline: Why n-day gaps and 90-day embargoes are failing in practice.
The traditional vulnerability disclosure timeline relies on a fundamental assumption: exploit development and vulnerability discovery take time. Over the last 12 months the integration of LLMs into offensive tooling has demonstrably broken this assumption. I recently published a technical write-up arguing that the 90-day disclosure window is effectively dead backed by three specific observations from recent incidents: 1. **Automated Diff Analysis (30-minute n-days) :** The safety net between a patch release and an in-the-wild exploit is gone. Taking a recent React security patch (CVE-2026-23870), I used an LLM to analyze the diff, identify the vulnerable path, and write a working DoS PoC in roughly 30 minutes. The human reverse-engineering bottleneck has been bypassed. 2. **Vulnerability Convergence :** I recently reported a critical P0 to a vendor and was told I was the 11th reporter in 6 weeks. LLM assisted scanners are causing independent researchers to converge on the same bugs simultaneously. An embargo no longer contains the vulnerability; it simply provides a head start to whichever threat actor also found it. 3. **The Linux Kernel (Copy Fail & Dirty Frag) :** The recent kernel exploits highlight this perfectly. Copy Fail (CVE-2026-31431) went from an automated AI scan to a public PoC to nation state weaponization in days. Shortly after the embargo for Dirty Frag (CVE-2026-43284 / CVE-2026-43500) was broken in hours because an unrelated third party independently discovered the same bug class using similar tooling. The defense cannot operate on monthly cycles when the offense is operating in hours. The focus needs to shift to real-time, PR-level AI scanning to match the pace. can read the full technical breakdown and case studies on my blog:[https://blog.himanshuanand.com/2026/05/the-90-day-disclosure-policy-is-dead/](https://blog.himanshuanand.com/2026/05/the-90-day-disclosure-policy-is-dead/) I am curious if the researchers here are experiencing similar convergence rates or if you view this as a temporary anomaly while legacy codebases are scanned with new tools.
Saturday, May 9
I built a realistic enterprise security architecture guide covering SPOFs, insider threats, and budget implementation
The website for the popular JDownloader download manager was compromised earlier this week to distribute malicious Windows and Linux installers, with the Windows payload found deploying a Python-based remote access trojan. [...]
I recently investigated an individual operating through Odysee and Telegram who is selling a malicious Android RAT known as EagleSpy V6.0, which appears to be a rebranded version of CraxsRAT. During the investigation: \\- I was financially scammed after payment \\- The seller blocked communication afterward \\- The malware infrastructure was analyzed in detail Technical analysis confirmed: \\- Banking phishing overlays \\- Crypto wallet credential theft \\- Telegram bot exfiltration \\- Remote shell execution \\- Keylogging \\- Camera/microphone access \\- GPS tracking \\- Ransomware components \\- DEX packers for AV evasion \\- Hidden update/backdoor mechanisms The repository also contained evidence of real victim infrastructure and compromised device information. The malware appears capable of targeting not only victims, but potentially even buyers/operators through embedded update systems and hidden control mechanisms. Relevant reports have already been submitted to platform abuse teams. Odysee channel involved: https://odysee.com/@justicerat:e Telegram: @JustIcedevs This post is intended purely as a cybersecurity awareness warning to help prevent additional victims. If moderators require technical validation or indicators of compromise, I can provide structured analysis details privately.
Plus: Meta officially kills encrypted Instagram DMs, the Trump administration targets “violent left wing extremists,” leaked documents reveal Russia's school for elite hackers, and more.
cPanel has released updates to address three vulnerabilities in cPanel and Web Host Manager (WHM) that could be exploited to achieve privilege escalation, code execution, and denial-of-service. The list of vulnerabilities is as follows - CVE-2026-29201 (CVSS score: 4.3) - An insufficient input validation of the feature file name in the "feature::LOADFEATUREFILE" adminbin call that could result
Friday, May 8
Existing benchmarks for LLM-based vulnerability detection compress model performance into a single metric, which fails to reflect the distinct priorities of different stakeholders. For example, a CISO may emphasize high recall of critical vulnerabilities, an engineering leader may prioritize minimizing false positives, and an AI officer may balance capability against cost. To address this limitation, we introduce SecLens-R, a multi-stakeholder evaluation framework structured around 35 shared dimensions grouped into 7 measurement categories. The framework defines five role-specific weighting profiles: CISO, Chief AI Officer, Security Researcher, Head of Engineering, and AI-as-Actor. Each profile selects 12 to 16 dimensions with weights summing to 80, yielding a composite Decision Score between 0 and 100. We apply SecLens-R to evaluate 12 frontier models on a dataset of 406 tasks derived from 93 open-source projects, covering 10 programming languages and 8 OWASP-aligned vulnerability categories. Evaluations are conducted across two settings: Code-in-Prompt (CIP) and Tool-Use (TU). Results show substantial variation across stakeholder perspectives, with Decision Scores differing by as much as 31 points for the same model. For instance, Qwen3-Coder achieves an A (76.3) under the Head of Engineering profile but a D (45.2) under the CISO profile, while GPT-5.4 shows a similar disparity. These findings demonstrate that vulnerability detection is inherently a multi-objective problem and that stakeholder-aware evaluation provides insights that single aggregated metrics obscure.
As a maintainer, this is Cilium's take on how we secure our Github Actions in the OSS project. A few highlights: * SHA pinning every GitHub Action * Separating trusted vs untrusted code paths in `pull_request_target` * Isolating CI credentials from production release credentials * Cosign signing + SBOM attestations * Vendoring Go dependencies to make supply chain changes visible in review * Treating blast radius reduction as the core design principle and a few gaps: * no SLSA provenance yet * remaining mutable [u/main](https://www.reddit.com/user/main/) references * no dependency review at PR time * missing govulncheck integration
Threat hunters have flagged a previously undocumented Brazilian banking trojan dubbed TCLBANKER that's capable of targeting 59 banking, fintech, and cryptocurrency platforms. The activity is being tracked by Elastic Security Labs under the moniker REF3076. The malware family is assessed to be a major update of the Maverick family, which is known to leverage a worm called SORVEPOTEL to
NVIDIA has confirmed in a statement for BleepingComputer that GeForce NOW user information has been exposed in a data breach. [...]
Attackers move faster than overwhelmed SOC teams can realistically investigate alerts. Prophet Security breaks down how AI can help analysts investigate alerts faster and focus on real threats. [...]
The attack on the Trellix source code repository disclosed last week has been claimed by the RansomHouse threat group, which leaked a small set of images as proof of the intrusion. [...]
A previously undocumented Linux implant codenamed Quasar Linux RAT (QLNX) is targeting developers' systems to establish a silent foothold as well as facilitate a broad range of post-compromise functionality, such as credential harvesting, keylogging, file manipulation, clipboard monitoring, and network tunneling. "QLNX targets developers and DevOps credentials across the software supply chain,"
The dark secret of enterprise security operations is that defenders have quietly institutionalized the practice of not looking. This is not just anecdotal, but rather backed by a recent report investigating more than 25 million security alerts, including informational and low-severity, across live enterprise environments. The dataset behind these findings includes 10 million monitored
Cybersecurity researchers have disclosed details of a new Linux backdoor named PamDOORa that's being advertised on the Rehub Russian cybercrime forum for $1,600 by a threat actor called "darkworm." The backdoor is designed as a Pluggable Authentication Module (PAM)-based post-exploitation toolkit that enables persistent SSH access by means of a magic password and specific TCP port combination.
With the launch of the first 16 satellites, Russia begins construction of a network for satellite internet that aims to cover the entire country by 2030. But getting there won’t be easy.
Details have emerged about a new, unpatched local privilege escalation (LPE) vulnerability impacting the Linux kernel. Dubbed Dirty Frag, it has been described as a successor to Copy Fail (CVE-2026-31431, CVSS score: 7.8), a recently disclosed LPE flaw impacting the Linux kernel that has since come under active exploitation in the wild. The vulnerability was reported to Linux kernel maintainers
Thousands of schools around the US were paralyzed on Thursday after education tech firm Instructure shut down access to its Canvas platform following a breach by hackers going by the name ShinyHunters.
SASS King Part 2: reverse-engineering ptxas heuristic decisions and what the compiled binary actually reveals
An ongoing data extortion attack targeting the widely-used education technology platform Canvas disrupted classes and coursework at school districts and universities across the United States today, after a cybercrime group defaced the service’s login page with a ransom demand that threatened to leak data from 275 million students and faculty across nearly 9,000 educational institutions. A screenshot shared by a reader showing the extortion message that was shown on the Canvas login page today. Canvas parent firm Instructure responded to today’s defacement attacks by disabling the platform, which is used by thousands of schools, universities and businesses to manage coursework and assignments, and to communicate with students. Instructure acknowledged a data breach earlier this week, after the cybercrime group ShinyHunters claimed responsibility and said they would leak data on tens of millions of students and faculty unless paid a ransom. The stated deadline for payment was initially set at May 6, but it was later pushed back to May 12. In a statement on May 6, Instructure said the investigation so far shows the stolen information includes “certain identifying information of users at affected institutions, such as names, email addresses, and student ID numbers, as well as as messages among users.” The company said it found no evidence the breached data included more sensitive information, such as passwo
A look at how to secure Kubernetes secrets
Thursday, May 7
Chrome users were caught off guard by a 4-GB Google AI model baked into Chrome, sparking privacy concerns. The good news: You can easily uninstall it. The bad? You might not want to.
This afternoon, we sent the following email to our global team. One of our core values at Cloudflare is transparency, and we believe it's important that you hear this directly from us because it’s a major moment at Cloudflare. Team: We are writing to let you know directly that we’ve made the decision to reduce Cloudflare’s workforce by more than 1,100 employees globally. The way we work at Cloudflare has fundamentally changed. We don’t just build and sell AI tools and platforms. We are our own most demanding customer. Cloudflare’s usage of AI has increased by more than 600% in the last three months alone. Employees across the company from engineering to HR to finance to marketing run thousands of AI agent sessions each day to get their work done. That means we have to be intentional in how we architect our company for the agentic AI era in order to supercharge the value we deliver to our customers and to honor our mission to help build a better Internet for everyone, everywhere. Today is a hard day. This decision unfortunately means saying goodbye to teammates who have contributed meaningfully to our mission and to building Cloudflare into one of the world’s most successful companies. We want to be clear that this decision is not a reflection of the individual work or talent of those leaving us. Instead, we are reimagining every internal process, team, and role across the company. Today’s actions are not a cost-cutting exercise or an assessment of individuals’ performance; they are about Cloudflare defining how a world-class, high-growth company operates and creates value in the agentic AI era. This is a moment we need to own as founders and leaders of the company. Matthew has personally sent out every offer letter we've extended. It is a practice he has always looked forward to because it represented our growth and the incredible talent joining our mission. It didn’t feel rig
Ivanti is warning that a new security flaw impacting Endpoint Manager Mobile (EPMM) has been explored in limited attacks in the wild. The high-severity vulnerability, CVE-2026-6973 (CVSS score: 7.2), is a case of improper input validation affecting EPMM before versions 12.6.1.1, 12.7.0.1, and 12.8.0.1. It allows "a remotely authenticated user with administrative access to achieve remote code
Cybersecurity researchers have disclosed details of a new credential theft framework dubbed PCPJack that targets exposed cloud infrastructure and ousts any artifacts linked to TeamPCP from the environments. "The toolset harvests credentials from cloud, container, developer, productivity, and financial services, then exfiltrates the data through attacker-controlled infrastructure while attempting
Palo Alto Networks has disclosed that threat actors may have attempted to unsuccessfully exploit a recently disclosed critical security flaw as early as April 9, 2026. The vulnerability in question is CVE-2026-0300 (CVSS score: 9.3/8.7), a buffer overflow vulnerability in the User-ID Authentication Portal service of Palo Alto Networks PAN-OS software that could allow an unauthenticated attacker
Bad week. Turns out the easiest way to get hacked in 2026 is still the same old garbage: shady packages, fake apps, forgotten DNS junk, scam ads, and stolen logins getting dumped into Discord channels like it’s normal. Some of these attack chains don’t even feel sophisticated anymore. More like some tired guy with a Telegram account and too much free time. The worst part is how often this stuff
Companies like Lovable, Base44, Replit, and Netlify use AI to let anyone build a web app in seconds—and in thousands of cases, spill highly sensitive data onto the public internet.
Having an incident response retainer, or even a pre-approved external incident response firm, is not the same as being ready for an incident. A retainer means someone will answer the phone. Operational readiness determines whether that team can do meaningful work the moment they do. That distinction matters far more than many organizations realize. In the first hours of a security incident
Wednesday, May 6
To stop children from bypassing its age checks, Meta is revamping its age-verification tools with an AI system that analyzes images and videos for “visual cues,” such as height and bone structure.
On May 5, 2026, at roughly 19:30 UTC, DENIC, the registry operator for the .de country-code top-level domain (TLD), started publishing incorrect DNSSEC signatures for the .de zone. Any validating DNS resolver receiving these signatures was required by the DNSSEC specification to reject them and return SERVFAIL to clients, including 1.1.1.1 , the public DNS resolver operated by Cloudflare. The country-code top-level domain for Germany, .de , is one of the largest on the Internet. On Cloudflare Radar , it consistently ranks among the most broadly queried TLDs globally. An outage at this level of the DNS hierarchy has the potential to make millions of domains unreachable. In this post, we’ll walk through what we saw, the impact of these events, and how we applied temporary mitigations while DENIC resolved the issue. How DNSSEC works DNSSEC (Domain Name System Security Extensions) adds cryptographic authentication to DNS. When a zone is signed with DNSSEC, each set of records is accompanied by a digital signature known as an RRSIG record that lets a resolver verify the records haven’t been tampered with. Unlike encrypted DNS protocols, such as DNS over TLS (DoT) and DNS over HTTPs (DoH), DNSSEC is about integrity, not privacy. The records are visible, but their authenticity can be proven. What makes DNSSEC unique is that the signatures travel together with the records they protect. This means int
It's not just you. Scammers, hackers, and other cybercriminals are complaining about “AI shit” flooding platforms where they discuss cyberattacks and other illegal activity.
BSides can often be the one place where you can find the most obscure talks about a technical detail. For example, "Edge Device Memory Forensics" by Richard Tuffin or maybe "Forensic analysis of privacy focused mobile browsers" by Lorena Carthy and Ruben Jernslett. Finding them is the hard part. I built a website that tracks all BSides chapters, all 8575 videos, fetches transcripts, indexes them by technology, speakers, events, tools, protocols, standards, and much more. It is free, no login, no ads, no tracking beyond basic visits (no cookies). And I'm planning to keep it so. Check out the forensics talks at [https://allbsides.com/talks.html?q=forensics](https://allbsides.com/talks.html?q=forensics), and let me know if you find the site useful or spot anything missing. Genuinely happy to receive feedback!
Someone hacked the deadmau5 discord server by virusing an admin. Said admin gave me the malware sample. Used claude sonnet 4.6 in combination with nyxstrike MCP framework to decompile and decrypt their obfuscated code, finding a goldmine. Title speaks for itself. The discord bot token could possibly have led to their CNC. But logging into the discord bot token to check for communications and see where it leads breaks 2 federal laws alone that I can think of. I did validate the token was live however, and matched it to a bot account. I also have discovered the webhook and token that was in the malware, both of them have been nuked (not by me). So, I checked their domain that they've been using, and they recompiled and reuploaded it. So its 26 bytes larger. I suspect they replaced the webhook url and the bot token with fresh ones, and suspect further that discord nuked the previous ones themselves. Nevertheless, I have personally not seen malware like this on github, so this must have been private and not some skid level stuff. I know it was turkish (at least the devs were). [Github](https://github.com/destiny-creates/goxlr.net-malware) link attatched for the source code including the deobfuscated malware classes, and the analysis/report. Don't flame me, it's still pretty cool 😆. Cracking the zkm encryption would have taken weeks (Im a python guy not a JS guy). Nyxstrike + sonnet 4.6 = 1.5 hours and its cracked.
Presently sponsored by: Report URI: Guarding you from rogue JavaScript! Don’t get pwned; get real-time alerts & prevent breaches #SecureYourSite It's a fascinating display of leverage: the ShinyHunters folks, with very limited resources and experience (their demographic will be teenagers to their early 20s), consistently gaining access to the data of massive brands. Not through technical ingenuity alone (although I'm sure there's a portion of that), but primarily through good ol' social engineering. That's coming through in the disclosure notices from the impacted companies, and Mandiant has a good write-up of it too : These operations primarily leverage sophisticated voice phishing (vishing) and victim-branded credential harvesting sites to gain initial access to corporate environments by obtaining single sign-on (SSO) credentials and multi-factor authentication (MFA) codes Question now is how long their run will go for. There's a very predictable ending if things keep going in this direction but right now, they show little sign of abating.
Tuesday, May 5
Hi all — finally pushed this public after several months of work. Sharing here because this subreddit is where I'd want feedback from before anywhere else. **WAInsight** — https://github.com/akhil-dara/WAInsight (MIT) **Scope.** It doesn't extract data from a phone — that's a separate step with whatever acquisition workflow you already use. WAInsight starts after acquisition. Point it at a folder containing `msgstore.db` + `wa.db` + `Media/` + `Avatars/` and it ingests everything through a 29-stage pipeline into a normalised `analysis.db` (47 indexed tables), then opens a 30-page Qt desktop UI to actually work the case. **Why.** I wanted analysis to be the primary deliverable, not the report. So the UI is built around browsing every chat exactly like opening WhatsApp itself — home-style conversation list, bubbles with edits / revokes / replies / reactions / receipts / forwarded badges / mention chips / pinned-message strip — with forensic provenance one click away on every bubble. Reports are a snapshot of what was found, not the destination. **Capabilities, grouped by what you're actually trying to do:** *Reading the timeline* - Forensic ℹ button on every bubble: msgstore source IDs, every SQL row that fed the bubble, origination flags decoded, per-recipient receipt timeline (delivered / read / played, ms-precise). - Ghost-message recovery from `message_quoted_text` (deleted-for-everyone messages reconstructed inline next to the revoked bubble). - Edit history per message — every revision side-by-side. - Reply chains as click-through badges with cross-conversation "Go to original" jumps. - 60+ system events decoded (group / security / admin / privacy / business / ephemeral) instead of opaque type codes. - Calendar with per-day message counts shown flight-fare style; click+drag to range-filter. - Windowed-flat virtual scroller for chats with 5K+ messages — jumping to message #47K in a 47K-message chat is O(1). *Media analysis* - Folder-shaped Media Dashboard that scales to 200K+ rows at `file://` (sharded AVIF thumbs + chunked metadata + vendored UI engine, sub-millisecond bitset crossfilter). Cascading filters: conversation × sender × MIME × extension × status × date. - Perceptual visual search across the whole case — drop a screenshot, get Exact / Near-Exact / Near-Duplicate / Template-Match tiers (pHash + dHash + edge-map). - Camera-original → WhatsApp tracking: feed an original from `DCIM/`, find every chat that photo was sent in even after WhatsApp's recompression changed the SHA-256. - View-once images and voice notes downloadable from the bubble even after on-device expiry (CDN URL + media_key, AES-CBC + HMAC). - Hash-link auto-rescue: missing media that shares a SHA-256 with another message's on-disk media gets auto-resolved (tagged `recovery_method='hash_linked'`, never confused with a real local copy). - `wa.db` thumbnail blob rendered as fallback when even the bytes are gone. - HD/SD twin pairs surfaced inline with cross-jumps. - Cross-chat propagation: right-click any media → every chat that shared the same SHA-256, chronologically. Says where the bytes were *first seen*, not just where they were last forwarded. - 12-state media recovery taxonomy preserved in every report and dashboard (`original` / `downloaded` / `hash_linked` / `orphan_recovered` / etc.). - Orphaned-media browser: files in `Media/` with no surviving message row + auto-rescue against surviving message hashes. *Identity & devices* - Per-message platform attribution from `key_id` — every bubble carries an inline tag (Android / iPhone / Web/Desktop / Companion #N), confidence-scored. The classifier was its own separate research piece — collected `key_id` samples across real devices on Android, iPhone, Web, and linked companions until the rules held up. Powers the Group Report's *Device Platform Usage* breakdown and the contact's *Device Sessions* tab. - Unified contact registry merged from 5 sources (`jid_map` ∪ `wa_contacts` ∪ `lid_display_name` ∪ group labels ∪ mention names) so every JID resolves to one canonical identity. - Owner-aware everywhere — `sender_id IS NULL` for owner messages gets joined to `case_metadata` so owner activity never surfaces as "Unknown" anywhere in the UI or reports. *Groups & communities* - Past-participant reconstruction from 3 sources: `group_past_participant` ∪ `group_member.is_current=0` ∪ message-presence inference (catches members the roster purged after a long enough gap). - Owner can-post / can-edit banner on every Group Info page, sourced from `chat.participation_status` + admin flags. - Community LID resolution + comment-author resolution even when WhatsApp only stored the LID. - Group Edit History with profile-picture diff. *Calls* - Synthetic call reconstruction: calls that have no `message` row in their conversation get virtual rows so they render in every participant's chat timeline at the right position. Group voice chats appear inside the group's chat even when WhatsApp didn't write a message row for them. *Cross-case pivots* - Cross-Contact Analysis: pick 2+ contacts, instantly see shared groups, calls between them, file SHA-256 hashes any of them shared in common, cross @-mentions, every conversation any of them appears in. Owner is a first-class pickable contact. - FTS5 global search with sender / conversation / date / ghost filters; results panel as a sidebar inside the chat with click-to-jump highlights. *Reports & handoff* - Per-group landscape-A4 PDF/HTML report: case+evidence provenance banner with source-DB SHA-256 hashes, group identity, owner role, top contributors / forwarders, device platform split, mentions network, activity heatmap, calls, locations (with live-share start/final coords), message-type taxonomy (Type 64/82/90/92/112/116 etc. mapped to readable labels), bot activity, former members. - Per-contact report with section picker. - Offline HTML viewer bundle — single ZIP, opens from `file://` with no Python or server. WhatsApp-Web-style chat list, full message rendering, FTS5-equivalent search. The case officer / opposing counsel can open it in any browser. - Tagged-messages export with three modes (full / tagged-only / tagged ± N day buffer). **Forensic integrity.** Source `msgstore.db` opened with three independent guards (`?mode=ro&immutable=1` URI + `SQLITE_OPEN_READONLY` flag + `PRAGMA query_only=ON`). Source files SHA-256 hashed at ingest. Every action journaled to a hash-chained `chain_of_custody.jsonl` — each entry's hash includes the previous one, so the audit trail is tamper-evident, not just append-only. Original IDs preserved (`message.source_msg_id`, `media.source_media_row_id`, etc.) so every analysis row links back to its msgstore.db / wa.db origin. Timestamps shown local + UTC in brackets so case timezone is unambiguous. **Honest caveats.** Android-only. No automated tests yet. Schema research was done sample-by-sample so there are likely edge cases on WA versions / Business app / regional builds I haven't seen — Business app support is on the roadmap. Validated primarily against my own personal-device datasets. Built solo. PySide6 + SQLite + ~85K lines of Python. There's a deepwiki for it too (https://deepwiki.com/akhil-dara/WAInsight) if you want a deeper architectural read before cloning. Would genuinely value feedback from anyone who works WhatsApp cases regularly — especially edge cases or schema variants that break it. Issues / DMs / comments all welcome.
EMBA v2.0.1 with interactive firmware dependency map available - Check it out and let us know what you are missing
IOCX v0.7.1 — robustness update focused on malformed PEs, hostile strings, and static‑analysis hardening
Pushed a new IOCX release (v0.7.1) that’s aimed at making the engine much harder to break during static analysis. The focus was adversarial behaviour: malformed binaries, corrupted PE structures, and intentionally hostile IOC‑like strings. If you work with weird samples, tooling pipelines, or large‑scale triage, this release makes IOCX more robust under hostile conditions. **New PE structural heuristics** Six new checks added to catch structural anomalies without blowing up the parser: * overlapping/misaligned sections * inconsistent optional headers (PE32 & PE32+) * broken entrypoint mappings * corrupted data directories * malformed import tables * general PE layout inconsistencies These aren’t detections — they’re deterministic, reason‑coded structural signals to keep analysis stable. **Expanded adversarial PE corpus** Added a full suite of malformed and corrupted PEs, including: * broken RVAs / invalid addressing * truncated Rich headers * fake UPX names + packed‑lookalikes * PE32/PE32+ hybrids * “franken‑PEs” combining multiple faults All outputs are snapshot‑validated to guarantee deterministic behaviour. **Adversarial coverage across all IOC categories** New hostile string fixtures now stress every extractor: * homoglyph + mixed‑script domains * malformed URLs and schemes * broken IPv4/IPv6 * noisy or near‑miss hashes * invalid Base64 * adversarial crypto strings (incl. Base58Check) * long/invalid Windows paths * malformed emails The goal: keep extraction predictable even when the input is intentionally messy. **Parser & extractor hardening** * stable on malformed PE structures * structured, JSON‑safe error metadata * improved domain/URL/crypto/hash extractors * deterministic output across platforms **Links** GitHub: [https://github.com/iocx-dev/iocx](https://github.com/iocx-dev/iocx) PyPI: [https://pypi.org/project/iocx/](https://pypi.org/project/iocx/) **Example** `pip install iocx` `iocx suspicious.exe -a full` If you’re doing malware triage, static analysis, or building automated pipelines that need predictable IOC extraction, v0.7.1 should be a noticeable stability bump. Happy to discuss edge cases or weird samples people want covered next.
We recently added a C/C++ security checklist to the Testing Handbook and challenged readers to spot the bugs in two code samples : a deceptively simple Linux ping program and a Windows driver registry handler. If you found the inet_ntoa global buffer gotcha or the missing RTL_QUERY_REGISTRY_TYPECHECK flag, nice work. If not, here’s a full walkthrough of both challenges, plus a deep dive into how the Windows registry type confusion escalates from a local denial of service to a kernel write primitive. Since we first released the new C/C++ security checklist, we also developed a new Claude skill, c-review . It turns the checklist into bug-finding prompts that an LLM can run against a codebase. It’s also platform and threat-model aware. Run these commands to install the skill: claude skills add-marketplace https://github.com/trailofbits/skills claude skills enable c-review --marketplace trailofbits/skills The Linux ping program challenge The Linux warmup challenge we showed you in the last blog post has an obvious command injection issue. #include <stdio.h> #include <s
I built a 100% browser-only EXIF viewer + metadata remover + image-forensics lab — no upload, no account, free
I've been working on this for the last few months and just wanted to share. It's a free browser-based tool for inspecting and removing metadata from photos, videos, audio, PDFs and Office documents — and it has a small image-forensics lab built in. Live: [https://midgardmud.de/tools/exif/](https://midgardmud.de/tools/exif/) Why I built it: every other "EXIF remover" online asks you to upload your private files to a server. That's the opposite of privacy. So I wrote one that runs 100% in the browser via the File API — your file never leaves your device. F12 → Network tab → drop a 50 MB photo → you'll see zero outbound requests. What it does: • Strips metadata from JPG/PNG/WebP/GIF/HEIC/TIFF, MP4/MOV/MKV/WebM/AVI, MP3/FLAC/OGG/WAV, PDF, DOCX/XLSX/PPTX • Privacy Risk Score 0–100 with per-file breakdown so you see what's actually leaking • 4 one-click privacy profiles (Anonymous / Social-safe / Keep camera / GPS-only) • Forensics: ELA, JPEG-Ghost re-save heatmap, DQT compression fingerprint, Noise + CFA/Bayer pattern (defensible alternative to AI-image detectors), Copy-Move clone detection, embedded-thumbnail audit, RGB histogram, hex viewer, structure inspector • SHA-256 + perceptual hash (pHash) per file • ExifTool-compatible JSON export • Per-tag EXIF editor + GPS spoofing for JPEG • C2PA self-signed Content Credentials • Works fully offline as a PWA after first visit • 19 languages Stack: vanilla JS, no framework, no build step, \~12k lines. libheif WASM lazy-loaded for HEIC. Web Worker for big videos so the UI stays responsive. Happy to answer anything about how the parsers work, why I avoided React, or how the JPEG-Ghost / Copy-Move detection is implemented. Feedback very welcome.
Monday, May 4
The Model We’ve Relied on Is Starting to Break Over the past 20 years, I’ve seen the threat landscape evolve from opportunistic attackers, to organized cybercrime, to nation-state campaigns. Each shift forced security teams to adapt. What’s happening right now is different. AI models coming out of Anthropic, OpenAI, Google, and X are rewriting the […] The post Sara AI Pentesting Is Now Generally Available: The Model Is Changing appeared first on Synack .