Check Point has warned of active exploitation of a critical vulnerability impacting Remote Access VPN and Mobile Access deployments that are configured to use the deprecated IKEv1 key exchange protocol. The vulnerability, tracked as CVE-2026-50751 (CVSS score: 9.3), is a case of a logic flow weakness in certificate validation that allows an unauthenticated remote attacker to bypass user
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Monday again. The weekend was meant to be quiet. It wasn't. Last week had poisoned packages, a broken AI helper, and a worm tearing through repos. The ugly part: basic tricks still worked. A chatbot got fooled. A bot token got leaked inside the malware. The same old mistakes showed up again. And while everyone chased the loud stuff, quieter attackers sat in inboxes for months, reading mail and
Microsoft has announced that Visual Studio Code (VS Code) will apply a two-hour delay before extensions for the integrated development environment (IDE) are updated automatically to a newer version in an attempt to tackle software supply chain threats. "When automatic updates are enabled, new versions are auto-updated two hours after they are published, adding an extra layer of protection
A new variant of the Gafgyt botnet called C0XMO is targeting DD-WRT router firmware and can move to other device types with various CPU architectures. [...]
WhatsApp has detected and stopped spear-phishing campaigns allegedly conducted by the NSO Group after investigating user reports of social engineering attacks. [...]
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Monday, June 8
2026 Verizon DBIR: vulnerability exploitation overtakes stolen credentials as #1 breach entry point for the first time in 19 years
Verizon's 2026 Data Breach Investigations Report dropped and a few numbers stand out: \- Vulnerability exploitation now 31% of initial access, surpassing stolen credentials for the first time in 19 years of the report \- Human element still present in 62% of breaches (up from 60%) \- Mobile-centric social engineering up 40% year over year \- Shadow AI use by employees tripled to 45% \- Third-party / supply chain involvement jumped 60%, now in 48% of breaches The mobile social engineering jump is the one I find most interesting. As people get better at spotting traditional email phishing, attackers are pivoting to SMS, voice, and messaging apps, and that's where most awareness programs still have the biggest gap. Where do you think the next investment should go: patching cadence, layered controls on mobile, expanding awareness beyond email, or something else?
WhatsApp has detected and stopped spear-phishing campaigns allegedly conducted by the NSO Group after investigating user reports of social engineering attacks. [...]
I’ve watched AI change three things in my world almost at once: how my team works, how our buyers make decisions, and how security teams decide what risk is actually real. Most days, that’s exciting. We lean on ChatGPT, Claude, Gemini, Perplexity, Copilot — pick your assistant — to research a market, size up a […] The post Human-in-the-Loop: Why Human Validation Is the Trust Layer AI Still Needs appeared first on Synack .
Fake Interview deploys stealthy cross platform (macOS/Windows) through npm package install in take home assessment
NPM supply chain hidden as main payload in a take home project for a fake job interview..
The code WIRED identified is gone from the latest version of Meta AI, the companion app for the company’s smart glasses. Meta won’t say why or whether it’s coming back.
Gogs has patched a critical security zero-day flaw that can allow attackers to compromise Internet-facing instances and access any repositories (including private ones). [...]
HTTP/2 HPACK amplification: detection signatures + the nginx/Apache directives that actually stop it (lab- & vps verified)
Open harness for authorized lab validation: Whole Project --> https://github.com/Leviticus-Triage/APEX-Ngin2dos Lab write-up on HTTP/2 **HPACK amplification** (the "HTTP/2 bomb" primitive) — studied across nginx, Apache httpd, Envoy, Pingora and IIS with hard 8 GiB memory caps. **For defenders:** - **Detect:** low wire-bytes / high header-count on HTTP/2; worker RSS climbing without a traffic spike and not receding after disconnects - **Apache-specific:** cookie-crumb merge path bypasses `LimitRequestFields` on pre-2.0.41 `mod_http2` - **Harden:** patch first (nginx ≥ 1.29.8 + `http2_max_headers`; httpd mod_http2 ≥ 2.0.41), then stream/conn caps, tighter timeouts, emergency HTTP/2 disable - **Verify:** authorization-gated harness to confirm your fix actually stops RSS climb (not just on paper) **Lab numbers:** httpd ~0.19 MB wire → 8 GiB; nginx ~200 MB → 8 GiB. Single-IP caveat: ~31 concurrent bombs from one public IPv4, no persistent OOM. Feedback on detection beyond rate-limiting welcome.
Attackers can chain three already fixed vulnerabilities in the Ubiquiti UniFi OS server to execute remote code with root privileges and without authentication. [...]
yo, wrote a blog regarding a macOS/Windows malware dubbed SstarAgent RAT deployed through fake job interview campaigns. Distribution relies on installing malicious npm package.
Check Point has warned of active exploitation of a critical vulnerability impacting Remote Access VPN and Mobile Access deployments that are configured to use the deprecated IKEv1 key exchange protocol. The vulnerability, tracked as CVE-2026-50751 (CVSS score: 9.3), is a case of a logic flow weakness in certificate validation that allows an unauthenticated remote attacker to bypass user
Came across this paper and thought it was worth sharing here since it addresses something that comes up a lot in ML-based detection discussions. The core problem it tackles: you cannot train a good detector for malware families you have not seen yet. By the time enough real samples of a novel strain exist to retrain your models, it has already done damage. This is one of the reasons signature-based and even ML-based detectors consistently struggle with zero-day malware. The practical value here is the counter-approach. Train a generative model on known malware behavior, let it learn the underlying statistical patterns, then use it to synthesize plausible variants that do not exist yet in the wild. Add those to your training data before you train your classifier. Your detector now has exposure to malware shapes it has never actually seen in the real world. They tested this on the CICMalDroid 2020 Android malware dataset using random forest, XGBoost, and a sequential neural network. Detection accuracy improved across all three, with the biggest gain on the sequential model at around 3.5%. Smaller but consistent improvements for adware and banking malware categories, which are exactly the categories where real-world sample volume tends to be thinner. What I found most relevant for defenders is the threat model it responds to. Attackers are already using AI to mutate and obfuscate malware faster than security teams can collect and label samples. This gives the defensive side a way to use the same generative technique to get ahead of variants rather than always chasing them. One honest caveat from the paper worth knowing: generative models can degrade over time if they are not fed new real samples. This works as a supplement to real data collection, not a replacement for it. Paper by Mohammad Alharbi from North Dakota State University and Jeremy Straub from the Center for Cybersecurity and AI at the University of West Florida.
Security teams are increasingly overwhelmed by alert fatigue, infrastructure maintenance, and complex hybrid environments. This article explores how Wazuh Cloud helps simplify SIEM/XDR operations through managed infrastructure, automated scaling, and AI-driven security analysis. [...]
Phishing has always been a numbers game. AI has turned it into a volume machine. Attackers can now create convincing emails, fake login pages, and tailored lures in minutes. Every polished message adds another case for Tier 1 to review, another link to inspect, and another alert that cannot be dismissed at a glance. As the queue grows, a credential theft attempt or malware delivery can easily
Monday again. The weekend was meant to be quiet. It wasn't. Last week had poisoned packages, a broken AI helper, and a worm tearing through repos. The ugly part: basic tricks still worked. A chatbot got fooled. A bot token got leaked inside the malware. The same old mistakes showed up again. And while everyone chased the loud stuff, quieter attackers sat in inboxes for months, reading mail and
Cloudflare’s Threat Events provides security analysts with a window into the global threat landscape. The platform offers a peek into the immense traffic that Cloudflare processes every day, so you can see in real time which IPs are attacking specific industries or which threat actors are trending globally. However, translating that visibility into active mitigation has often been a manual, reactive process. Security teams have faced a recurring frustration: knowing that certain IP addresses were associated with specific threat actors (like Tycoon 2FA or RaccoonO365 ) or had been seen targeting their specific industry in other regions, but they couldn't easily automate the blocking of these high-risk IPs within their own WAF unless they manually configured the rules. We are excited to announce a new integration that brings Cloudflare’s vast threat intelligence directly into your WAF engine: you can now write proactive rules using live intelligence data . This means you can add more intelligence context to protect your application against known bad actors — before they even attempt to touch your infrastructure. By populating specialized fields during the early stages of a request, the WAF can now screen traffic based on: Who is attacking by matching specific threat actor names Who they are targeting via the industry or country filters to see who the IP has targeted in the past What type of attack using enriched
Socket researchers disclosed a June 7, 2026 PyPI supply-chain campaign where attackers compromised 19 legitimate scientific research and deep-learning packages. The malware abuses Python startup hooks (\*-setup.pth) to execute automatically, bootstrap Bun, and steal credentials.
Mythos is real. I know a big chunk of the industry thinks it's a marketing stunt, and I get why. I get it. But I've seen the findings, and they're bad. These aren't "whoops, this line right here is wrong, and that's RCE." They're novel combinations of a few dozen issues out of thousands of things every SAST scanner already finds, chained together into something much worse. It's real creativity,
COPENHAGEN, Denmark, June 8, 2026 – Heimdal has achieved ISAE 3000 SOC 2 Type II certification for the sixth consecutive year, reflecting the company’s continued focus on operational security, accountability, and data protection. The 2026 audit covered the period from 1 April 2025 to 31 March 2026 and examined Heimdal’s controls across access management, data […] The post Heimdal® Marks Six Years of Consecutive ISAE 3000 SOC 2 Type II Certification appeared first on Heimdal Security Blog .
The University of Oxford disclosed a new data breach last week after being informed by its third-party provider, Group GTI, that its CareerConnect career services platform had been compromised. [...]
A China-nexus cyber espionage group has been observed deploying a BSD variant of a known backdoor called BRICKSTORM, as well as two other malware families codenamed PLENET (aka GRIMBOLT) and AGENTPSD to target Linux systems. The activity has been attributed by Volexity to a threat cluster it tracks as VerdantBamboo, which it said overlaps with hacking groups known as Clay Typhoon (Microsoft),
Cybersecurity researchers have disclosed details of a financially motivated data theft extortion campaign that has targeted dozens of organizations across professional, legal, and financial services in the U.S. between January and May 2026. The activity has been attributed by Google Mandiant and Google Threat Intelligence Group (GTIG) to a threat actor dubbed UNC3753, which is also known as
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.
Microsoft has announced that Visual Studio Code (VS Code) will apply a two-hour delay before extensions for the integrated development environment (IDE) are updated automatically to a newer version in an attempt to tackle software supply chain threats. "When automatic updates are enabled, new versions are auto-updated two hours after they are published, adding an extra layer of protection
A WIRED timeline shows how dozens of governments, companies, and other organizations across Europe are moving, or planning to shift, away from US Big Tech.
[https://github.com/ahmaaaaadbntaaaaa-byte/TID-Instant-Destroyer](https://github.com/ahmaaaaadbntaaaaa-byte/TID-Instant-Destroyer)
Sunday, June 7
Microsoft has created an open-source fork of Windows Terminal called "Intelligent Terminal," and it allows you to use AI directly inside Terminal without interfering with the regular session. [...]
Slapping an LLM onto a security tool without guardrails is a massive liability. In digital forensics and incident response (DFIR), an AI hallucination can ruin an entire chain of custody. An answer without mathematical, binary proof is completely worthless. If an AI agent cannot anchor its reasoning to exact offsets, hashes, and unmanipulated timestamps, it has no business touching forensic data. With **Crow-Eye v0.11.0**, we are pushing a massive update to our full-spectrum forensic lifecycle platform. This release introduces a hardened AI compliance architecture and completely upgrades the core correlation engines. We are treating the underlying intelligence layer like a highly supervised junior analyst. Everything it sees is hashed, everything it thinks is visible, its memory management is strictly audited, and its ability to alter rules is completely sandboxed. Here is exactly how we are enforcing forensic integrity under the hood in v0.11.0: # 1. AI Compliance & Governance # Evidence Seal & Cryptographic Chain of Custody Every single time the AI interacts with your forensic data, it is cryptographically verified. * **The Process:** Before any payload is passed to the AI model, the `evidence_seal.py` service steps in. * **Hashing & Provenance:** It calculates the SHA-256 hash of the exact bytes being sent and attaches metadata tracking the absolute source (e.g., `database:table:rowid`), token count, and the specific AI model used. * **Hash-Chaining:** This metadata is written to an append-only JSONL ledger. Each new record incorporates the hash of the previous record. If a single byte of historical evidence is tampered with, the entire cryptographic chain breaks instantly. # The TruncationAuditor Service (Context Auditing) AI context windows are a massive compliance bottleneck. Silent truncation—where a tool quietly drops data when limits are exceeded—is unacceptable in an investigation. The `TruncationAuditor` service acts as a strict forensic bookkeeper to log exactly how history is modified during our Self-Healing Context routine. * **The Append-Only Audit Log:** Events are permanently written to `<case>/EYE_Logs/truncation_audit.log`, tracking whether data was compressed (`SUMMARIZED`) or entirely removed (`TRUNCATED`). * **High-Fidelity Tracking:** Every single dropped or compressed message records its unique Message ID, token count, reason (e.g., `budget_exceeded`), extra JSON metadata, and a SHA-256 Content Hash of the exact message text to mathematically prove what was removed. * **Tamper-Evident Hash-Chaining:** Each log entry combines its content with the hash of the previous log line using a `chain=...` signature. If a rogue actor manually deletes a record from the text log to hide missed evidence, the chain breaks instantly, and the `verify_chain()` check fails. * **Protocol Compliance Panel:** The auditor exports this ledger into a structured JSON array (`audit_trail.json`). The React UI reads this to give investigators a clean visual timeline of exactly what was preserved, summarized, or dropped. https://preview.redd.it/7yysi31xgu5h1.png?width=3394&format=png&auto=webp&s=16032abda1bbbccd2986be1479e37a0c45ec5a69 # The ThinkingStep Protocol (Anti-Black-Box Streaming) The AI is hard-coded to "show its work." The `ThinkingStep` protocol bridges the Python backend (`eye_bridge.py` and `query_processor.py`) and the React frontend (`EyeDialogue.tsx`), streaming real-time updates over `QWebChannel` across 4 distinct, auditable phases: * **Phase 1: thinking (Intent Detection):** The backend queries the LLM to determine intent (e.g., separating general questions from direct MFT queries). The UI displays "Analyzing request..." * **Phase 2: rag (Retrieval-Augmented Generation):** The backend searches local forensic rules inside `configs/knowledge_base/` (like pulling up Living off the Land tactics for PowerShell analysis) and shows you exactly what was fetched. * **Phase 3: tool\_call (Execution):** If the AI needs hard data, it sends a structured command to the backend to fire off a tool (e.g., executing a raw SQLite database query). The UI displays a dedicated "Tool Execution" block exposing the exact arguments, execution status, and raw JSON payloads returned. This layer loops sequentially if multiple tools are required. If a tool fails on a bad SQL query, the step turns red, exposes the raw Python exception, and allows the AI to catch the error in its context to heal and try a corrected query. * **Phase 4: synthesis (Final Generation):** The backend bundles the RAG knowledge and tool results securely using the Evidence Seal, routing them to the model to stream out the final human-readable response. * **UI Transparency:** In the frontend, these phases are rendered as interactive, collapsible accordion blocks. You can expand a tool block to verify every database query syntax or piece of documentation the AI used before arriving at its final conclusion. # Governance Enforcement Protocols (GEP Rules 9-11) When the AI acts as an author (like generating correlation rules), it is locked down: * **Reasoning Required (R9):** The AI cannot create or edit any rule without rendering a clear text justification. * **Evidence Linking (R10):** The AI cannot hallucinate a rule. It must bind it back to the exact physical forensic artifact (`related_evidence`) that prompted it. * **Read-Only Built-ins (R11):** The AI is strictly sandboxed from modifying human-authored rules or built-in system defaults. # 2. Core Engine Upgrades With the AI heavily supervised, v0.11.0 also delivers massive architectural upgrades to the data engines feeding the platform. **Advanced Core Correlation Engine Upgrade** An adversary leaves footprints across multiple layers of the system simultaneously. * **Deep Artifact Stitching:** Crow-Eye automatically maps the connective tissue between Master File Table (MFT) records, Registry hives, LNK files, and Jump Lists. * **Instant Timeline Reconstruction:** The engine identifies non-obvious relationships instantly, allowing you to trace an execution lifecycle from initial file access straight to system persistence without manual cross-referencing. **Ironclad Identity Engine Upgrade** Attributing actions to specific security identifiers (SIDs) in modern Windows 11 environments can get incredibly messy during high-stress triage. * The upgraded **Identity Engine** brings precise, deterministic execution-context tracking. It resolves user sessions, elevation states, and mapped SIDs with absolute certainty, eliminating ambiguity during credential abuse investigations. For the next release, I am focusing completely on user bugs and performance edge-cases. Please feel free to contact me for any bug reports or support queries you can find all of my direct contact details on the official website:https://crow-eye.com/ **GitHub:**[https://github.com/Ghassan-elsman/Crow-Eye](https://github.com/Ghassan-elsman/Crow-Eye) for the full details of the Resale notes please check [https://github.com/Ghassan-elsman/Crow-Eye/releases/tag/0.11.0](https://github.com/Ghassan-elsman/Crow-Eye/releases/tag/0.11.0) Good hunting,
A new variant of the Gafgyt botnet called C0XMO is targeting DD-WRT router firmware and can move to other device types with various CPU architectures. [...]
The Silent Ransom Group extortion gang is actively targeting U.S. law firms and professional services organizations in social engineering attacks that often lead to data theft within hours of initial contact, according to a new report by cybersecurity firm Mandiant. [...]
EDRChoker uses **Policy-based Quality of Service (QoS)** to set hard bandwidth caps (throttling) on Endpoint Detection and Response (EDR) agents, causing them to always time out - effectively blocking them.
I recently learned about multiple sandbox bypasses discovered in Twig by project Glasswing. From the descriptions, only CVE-2026-46640 and CVE-2026-46633 seemed universally exploitable, so I decoded to research them. This writeup documents my development of payloads for the CVE-2026-46640 and the corresponding SSTImap module.
Saturday, June 6
OpenAI has begun rolling out a new Lockdown Mode to ChatGPT for eligible personal accounts to reduce the risk of data exfiltration arising from prompt injection attacks. The feature is primarily designed for people and organizations that handle sensitive data and require stricter protection guarantees. Lockdown Mode is available to logged-in users across Free, Go, Plus, and Pro, and
Plus: Hackers use Meta’s AI bots to hack Instagram accounts, Anthropic helps NSA hackers, a decades-long GPS satellite mystery may have been solved, and more.
A researcher has reverse-engineered the iOS SDK that Bright Data embeds in consumer apps and documented how it turns devices, including always-on smart TVs, into exit nodes that relay web-scraping traffic for a data business Bright Data markets heavily to the AI industry. The company, the successor to Luminati, operates what it calls the largest residential proxy network in the world,
Two things landed within days of each other this week. A security startup reported 21 previously unknown vulnerabilities in FFmpeg, the media library inside almost everything that touches video, all of them found by an autonomous AI agent. The same week, Google shipped Chrome 149 with patches for 429 security bugs, the most ever in a single release. Only the FFmpeg bugs were found by AI.
Friday, June 5
Tech giant Toshiba and mega-retailer Muji warned visitors that suspicious sign-in screens popping up on their websites could collect credentials. [...]
CISA warned today that hackers are now actively exploiting a recently patched high-severity SolarWinds Serv-U flaw to crash servers. [...]
A Chinese espionage group tracked as UNC5221 has been accessing Microsoft 365 environments using the Brickstorm backdoor and previously undocumented malware named Plenet and AgentPSD. [...]
A California man was sentenced to more than 26 years in federal prison for trafficking fentanyl and methamphetamine through Nemesis Market, one of the world's largest dark web marketplaces. [...]
At Gartner SRM 2026 this week I gave a talk called “Cutting Through AI Noise: Defending Against Machine-Speed Cyber Adversaries.” The room was full of security leaders who’ve been through enough hype cycles to be skeptical of seeing AI on the label. That skepticism is warranted, and I built the session around it. Here’s what […] The post What I Told Security Leaders at Gartner SRM 2026 appeared first on Synack .
Arabic-speaking users have emerged as the target of a new Android spyware codenamed Asin, according to findings from ESET. The Slovakian cybersecurity company said it first detected the malware spread via multiple campaigns in early 2025, with each attack wave making use of distinct websites mimicking utilities, war-related updates, and a government news source: govlens[.]net, which
There isn't a CIO on the planet not worried about AI spend right now. CFOs are increasingly nervous, too. For fear of falling behind, many companies have pushed their employees to use AI as aggressively as possible. The edict was clear: "Move fast, we'll figure out the bill later." And for the most part, it worked: AI has been genuinely transformational for the teams that leaned in. But the costs are real: we’ve heard countless horror stories of huge bills and painful overages on token spend. Today, we're announcing spend controls in Cloudflare AI Gateway, and a closed beta for identity-driven budgets and routing using Cloudflare Access and your existing identity provider. As we’ve spoken with hundreds of companies about their AI strategy, we’ve seen a common story: The company gives every engineer access to frontier models through a shared API key. Usage takes off. At the end of the month, finance pulls the invoice and nobody can explain where the money went. Was it the machine learning team training a new pipeline? Was it an intern running Claude Opus on email triage? Was it a runaway continuous integration job that burned through 50 million tokens in a weekend? Nobody knows, because the API key doesn't tell you who used it. Without guidelines, staff will generally reach for the biggest model available. And why wouldn't they? If there's no budget, no visibility, and no routing logic, the rational move is to use the most powerful model for everything. The problem is that most tasks don't need a frontier model. A code review summary doesn't need the same model as a complex architecture refactor. A log parser doesn't need the same model as a customer-facing content generator. It should be easy to select the right tool for the job, rather than defaulting to the most powerful and expensive one. And it should be simple to see where the spend is going. You can't calculate ROI on your AI spend without visibility on wh
Cybersecurity researchers have discovered a previously unreported threat cluster dubbed OP-512 (where "OP" stands for "opponent") that has been observed targeting Microsoft Internet Information Services (IIS) servers to deploy a bespoke web shell framework. ReliaQuest has assessed with moderate to high confidence that the espionage-focused activity is linked to China. "OP-512 was highly
Only 10% of SOCs Say They’re Getting Excellent Value From AI. Here’s What the Second Wave Has to Deliver
Eighteen months ago, the AI SOC was a marketing line. Today it's a budget item. The category has crossed over from interesting to inevitable, with billions of dollars now flowing into AI-powered security operations platforms, agentic SOC tools, and AI co-pilots built into every layer of the security stack. The data shows SOCs are buying, deploying, and standing up AI capabilities at the fastest
Thursday, June 4
In our last post we used a Claude skill to systematically beat down VirusTotal detection rates on offensive security tools, with a brief mention of a new loader we’d been using to apply those techniques in bulk. This post is about that loader, which we call WasmForge. WasmForge is, from the user’s perspective, a build wrapper. You point it at a Go project and you get back a Windows or macOS binary that runs your tool but doesn’t look anything like it. Internally it’s a lot more. It’s a Go-to-WebAssembly compiler, a custom Wazero fork, around eighty host shim functions for MacOS and Windows APIs, and a healthy amount of evasion techniques from our previously discussed skill. The whole pipeline exists to solve one specific problem: take an existing offensive security tool, change zero lines of its source code, and produce a binary you can actually drop on a hardened endpoint. The Tool Authors Won, Then The Tool Authors Lost Many red team engagements can be completed using the same handful of established tools. Sliver for
VoidZero, the company behind Vite , Vitest , Rolldown , Oxc , and Vite+ , is joining Cloudflare. As part of this change, all team members of VoidZero are joining Cloudflare, too. Before saying anything else, we want to make the most important thing clear: Vite, Vitest, Rolldown, Oxc, and Vite+ will stay open source, vendor-agnostic, and community-driven. Nothing about that changes. Cloudflare's mission is to help build a better Internet. And a better Internet is an open Internet. Developers need choice, frameworks need a neutral foundation, and applications need to be portable. It is not reasonable to expect the entire web ecosystem to build around a single vendor. The most important tools and frameworks are portable by design. Vite is one of the few foundational tools that the whole JavaScript ecosystem agrees on. It earned that position by being fast, excellent, portable, and vendor-neutral. One of the best ways Cloudflare can help build a better Internet is by investing in that foundational open source toolchain. A toolchain that makes the Internet better for everyone, not just people who use Cloudflare or choose to host with us. Over the last few years we've invested heavily in making Cloudflare the best place to build and run websites, applications, and agents on our developer platform . But ultimately that choice will always be yours. Run your Vite application anywhere you want. What this means for Vite Today's news gives Vite more resources to keep growing, while the things that make Vite what it is remain the same: Vi
At Accenture’s scale, training alone cannot solve every security problem. That was the reality facing Kris Burkhardt, Global CISO at Accenture. With a workforce of more than 800,000 people, close to 80,000 new hires each year, and a sprawling global attack surface, traditional penetration testing was no longer enough. A once-a-year compliance audit may check […] The post How Accenture Turned Penetration Testing Into a Force Multiplier for Security appeared first on Synack .
Learn four practical ways GreyNoise improves SOC outcomes—from reducing alert volume and surfacing targeted threats to identifying compromised hosts.
Wednesday, June 3
Four people suing Elon Musk's AI firm under pseudonyms due to the risks of being identified may face a difficult choice: Reveal your real names, or drop the lawsuit.
VU#595768: Securly Chrome Extension contains multiple weak encryption and access control vulnerabilities
Overview Version 3.0.7 of the Securly Chrome Extension contains multiple vulnerabilities involving insecure data transmission, weak cryptography, and improper access control. These issues may expose sensitive filtering rules, enable the manipulation of downloaded configuration files, and allow unauthenticated access to protected resources. An attacker could exploit these weakness to steal configuration information, induce a Denial of Service (DoS), or modify content blocking rules for student users. Description The Securly Chrome Extension is a browser add-on commonly used in K–12 school-managed Chromebooks to enforce internet safety policies, filter or block websites, and provide activity monitoring for students. It is an element of the Securly classroom management platform, which helps schools comply with web filtering requirements and safely manage student online access. CVE-2026-8874 Version 3.0.7 of the Securly Chrome Extension downloads JSON files containing crisis alert keywords and filtering rules over unencrypted HTTP via the Fetch API. Other endpoints in the same extension correctly fetch Internet Watch Foundation (IWF) and Children's Internet Protection Act (CIPA) data over HTTPS, demonstrating an inconsistent implementation of TLS. CVE-2026-8876 The Securly Chrome Extension contains hardcoded, plaintext AES passphrases in securly.min.js . These keys decrypt crisis alert keyword data and intervention site data. CVE-2026-8878 The Securly Chrome Extension exposes multiple publicly accessible endpoints that allow unauthenticated access to sensitive data. The exposed information consists of SHA-1 hashes that are inadequately obfuscated using a simple Caesar ciph
Some recent route hijacks reported by Spamhaus captured our attention. In many of these hijack attempts, an apparent bad actor took advantage of unused autonomous system numbers , or ASNs. Notably in these hijacks, the actor appears to be creating fake AS_PATHs toward destinations, misdirecting traffic down an unexpected path. By creating forged AS_PATHs, the hijacker is attempting to lead traffic somewhere it isn’t normally meant to go while also trying to conceal their identity. A hijacker could strip enough information away from a network path that they could pretend to be the origin of a Border Gateway Protocol (BGP) prefix themselves. Attackers can use this hijacked route to intercept traffic and for other nefarious purposes. There is a simple solution for these cases: basic verification that a BGP peer autonomous system (AS) always includes their network as the “First AS” in an advertised route. To get a sense of how well these safeguards are implemented, we stress-tested several major networks and researched their BGP implementations. Read on to see what we learned. Examining route hijacks involving forged paths The idea that an actor is creating fake AS_PATHs is supported when we take a closer look at implausible AS relationships in the path. For example, let’s examine one of the hijacks reported by Spamhaus, involving a prefix belonging to Orange S.A., the French telecom company. Using the monocle tool, we can
🚨 PCPJack's SMTP Toolkit Dissected: 3 Deployer Generations, Multi-Arch Chisel, and a Full EHLO/STARTTLS Verification Loop
PCPJack left a 12-file toolkit sitting on an open C2 directory, port 8444, no auth. Three multi-arch Chisel binaries, a Sliver-integrated deployer with three visible generations of iteration, and a persistent daemon handling EHLO/STARTTLS verification before enrolling hosts into the relay pool. One deployment wave, 230 beacons confirmed in state logs. Complete toolkit dissection, three deployer generations, and binary analysis here: [https://hunt.io/blog/pcpjack-230-cloud-servers-smtp-proxy-network-sliver-chisel](https://hunt.io/blog/pcpjack-230-cloud-servers-smtp-proxy-network-sliver-chisel)
I recently analysed a malvertising campaign where the attackers are using ChatGPT / OpenAI branding to deceive users into downloading malware. https://evalian.co.uk/fake-chatgpt-malvertising-campaign/
Public skill marketplaces are being flooded with malicious skills that steal credentials, exfiltrate data, and hijack agents. In response, a segment of the security industry released skill scanners, a new family of tools designed to detect malicious skills before they’re installed. But we tested them, and they don’t work. We recently bypassed ClawHub’s malicious skill detector , Cisco’s agent skill scanner , and all three of the scanners integrated into skills.sh . These were not advanced attacks: it took us less than an hour to conceive and implement three of the four malicious skills in trailofbits/overtly-malicious-skills , using standard tricks and rapid inspection of the scanner source code. The fourth malicious skill took a few hours, but only because the prompt injection required some trial and error. Our findings demonstrate that even when skill scanners have some defenses, their static nature gives an adversary unlimited bites at the apple to tweak an attack until it finds a way through. Why skill security matters Software supply chains have long been the soft underbelly of computer security. As fragile infrastructure susceptible to both insider threats and external attackers, these supply chains were vulnerable enough when malicious code was the sole vector of compromise. But the rise in agentic systems has spawned a new style of dependency—the skill—and with it a whole new ecosystem of marketplaces and distribution channels that now run alongside traditional package managers. Malicious skills can embed harmful instructions in nat
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 46th government onboarded to Have I Been Pwned’s free gov service: the Philippines. The Philippines’ National CERT, working with the Department of Information and Communications Technology, now has access to monitor official government domains against the data in HIBP. This gives their Cyber Threat Intel and Monitoring Section the ability to identify exposure across government email addresses and respond quickly when those accounts appear in new data breach. This is precisely what the HIBP government service was built for: helping national cyber teams better understand credential exposure across their government domain space, monitor for compromised accounts on demand via API, and receive notifications when government domains are impacted by newly loaded breach data. The Philippines joins a growing list of national CERTs and government cybersecurity teams using HIBP to help strengthen national cyber defense, protect government departments and resources, and reduce the risk posed by compromised credentials before attackers can take advantage.
Tuesday, June 2
Available for Android 12 and later, the anti-scam feature is baked into Google Dialer, which sends a silent “confirmation signal” to ensure whoever’s calling you is who they appear to be.
Overview VoLTE deployments on Verizon’s IMS network have operated without negotiated SIP integrity protection. In observed test conditions, SIP signaling—including registration, call setup, and messaging—traveled without IPsec ESP encapsulation and without SIP Security Agreement headers, exposing it to interception and modification by on-path attackers. Recent carrier configuration updates, including Apple’s iOS 26.5 carrier bundle released on May 11, 2026, include IMS IPsec–related settings. However, such configuration entries do not confirm active deployment, successful negotiation, or functional protection in production. Description CVE-2026-10629 Verizon IMS deployments were observed transmitting SIP signaling without integrity protection. REGISTER exchanges lacked Security-Client, Security-Server, and Security-Verify headers, and no ESP-encapsulated SIP traffic was detected during subsequent signaling such as INVITE, MESSAGE, BYE, and UPDATE. This pattern persisted across devices, operating systems, and network conditions, indicating a deliberate network configuration rather than a transient issue. Per 3GPP TS 33.203 and GSMA IR.92, SIP signaling between the UE and P-CSCF must be protected using IPsec ESP following IMS AKA authentication, with negotiation occurring during registration. The absence of this protection allows attackers to manipulate SIP signaling undetected, enabling call hijacking, spoofing, denial-of-service, and misrouting of emergency calls. Verizon initially acknowledged the issue and stated that integrity support would be available upon request and extended broadly later in the year. However, the company has since ceased participation in coordination, including follow-up discussions and draft review, and has not provided verifiable evidence of mi
Overview A stored cross-site scripting (XSS) vulnerability has been discovered in Appsmith, specifically in the CodeMirror based SQL query editor’s autocomplete renderer. CVE-2026-7299 has been assigned to track the vulnerability. An attacker with developer level access to a shared PostgreSQL datasource can inject arbitrary JavaScript by creating malicious database objects whose names contain XSS payloads. Successful exploitation leads to arbitrary JavaScript execution in the browser of any workspace member who triggers SQL autocomplete, enabling session hijacking, privilege escalation, or credential theft. Version 2.1 of Appsmith fixes CVE-2026-7299. Description Appsmith is an open source, low code platform intended to allow developers to build internal tools, dashboards, and applications using a UI builder, database and API integrations, and JavaScript customization. Appsmith can also be deployable either self-hosted or via the cloud. A vulnerability, tracked as CVE-2026-7299, has been discovered, allowing for XSS within the SQL query editors autocomplete function. The vulnerability description is below. CVE-2026-7299 Appsmith’s SQL query editor’s autocomplete functionality fails to sanitize database object names before rendering them in innerHTML, allowing an authenticated Developer to inject persistent XSS by a malicious table or column names triggering arbitrary code execution in the sessions of other workspace members when they interact with the same datasource. This vulnerability requires an account with developer access. A developer Appsmith account is an account designed to create, edit, and delete apps within a workspace they are assigned to. When an administrator opens the SQL editor and triggers autocomplete (e.g., by typing SELECT * FROM), the malicious ta
Overview The Collibra Platform Agent contains vulnerabilities that can be chained by a remote, unauthenticated attacker to achieve remote code execution. An attacker can exploit these issues by uploading a crafted ZIP archive that writes attacker-controlled files to arbitrary locations on the server once extracted, resulting in code execution. Description Collibra Platform (CP) and Collibra Platform Self-Hosted (CPSH), an enterprise grade, cloud-based platform designed to help organizations locate, understand, trust, and manage their data assets. The Collibra Agent of CP and CPSH that is installed on the host system is an independent service that listens on different port than the web interface and have the following vulnerabilities. CVE-2026-10622 Privileged REST endpoints exposed under /rest/* do not properly enforce authentication or authorization. This allows a remote, unauthenticated attacker to interact with sensitive application functionality and gather information useful for further exploitation, including identifying suitable filesystem locations or application paths. Additionally, the web services hosting the vulnerable REST endpoint was observed to bind to all available network interfaces regardless of the setting passed to the installer script. This behavior may increase exposure in deployments where administrators believe access is restricted to specific interfaces or trusted networks. CVE-2026-10621 A Zip Slip vulnerability during extraction is exposed through POST /rest/restore and enables path traversal. When a ZIP archive is processed, file paths contained within the archive are not properly validated or canonicalized before extraction.
The right-wing think tank is actively pushing “civil terrorism”—increasing penalties for minor crimes committed while people engage in constitutionally protected free speech.
Attackers are abusing the shared content features of AI chatbot platforms — ChatGPT and Claude — to deliver malware through pages hosted on legitimate, trusted domains, distributing the malicious links via sponsored malvertising ads on search engines.
Monday, June 1
Came across an article, product like phpBB still has some potential flaws.