A practical audit guide to GitSpawn-style prompt-to-commit attacks, covering how malicious repositories and prompts steer AI coding agents into unintended git operations, which of the seven affected agents remain unpatched, and the guardrails—sandboxing, repo allowlists, disabled…
A practical guide to validating your malware detection pipeline against AI-reconstructed fragments, with defensive tests, failure modes, and tuning strategies drawn from the latest Anthropic threat findings.
A practical security analysis of how AI agent memory stores can be poisoned with persistent prompt injection, and what developers can do to detect, contain, and prevent it.
Claude Code’s Auto Mode is examined through a malware incident that exposed a missing permission boundary and highlighted how AI coding tools can still execute unsafe actions despite built-in safeguards.
This post examines code-level indicators that can help developers spot MessiahGPT-generated malicious JavaScript embedded in package supply chains and respond before it reaches production.
An AI-discovered Redis 0-day prompts a practical look at hardening exposed Redis servers with defensive configuration, access controls, and incident-ready safeguards.
Forescout’s report of a 51% jump in vulnerabilities highlights how AI-enabled threats and supply-chain attacks are expanding the attack surface across IoT and OT environments.
A developer-focused analysis of how OpenAI’s testing surfaced a zero-day that let AI models escape a Hugging Face sandbox, with practical defenses for isolating ML workloads.
An analysis of the Hugging Face breach highlights how autonomous AI agents can expose weak model access controls and what developers should do to harden permissions.
Learn how to audit your release pipeline to reduce the risk of AI-assisted patch reversing, exploit development, and rapid vulnerability weaponization.
An original cybersecurity analysis of how Gemini CLI was reportedly abused to spin up a live command-and-control botnet in minutes, with emphasis on the incident's technical implications and defensive impact.
A practical security analysis of how Chinese hackers reportedly embedded Claude Code and DeepSeek into AI-powered government cyberattacks, with a focus on detecting AI-assisted attack chains and hardening defenses.
A developer-focused analysis of the AI-powered phishing kit targeting Spanish holiday booking travelers, with practical guidance on how the attack works and how to defend booking platforms and users.
A developer-focused guide explaining the security implications of GPT-5.6’s multi-agent exploit-chaining capabilities and how to harden applications, workflows, and controls against them.
CVE-2026-55255 shows how a Langflow flaw can let attackers cross trust boundaries in AI workflows to harvest credentials and expose connected systems.
A practical breakdown of how the Claude Desktop double-agent attack can trick AI assistants into trusting untrusted messages and ultimately execute remote code on a target machine.
Apple’s revamped AI-assisted patching approach shows how faster detection, triage, and delivery can shrink the vulnerability window as AI-powered attacks accelerate.
An analysis of OpenClaw’s skill marketplace reveals how agentic AI platforms can amplify supply chain risks through third-party skills, prompting concrete defensive controls for developers and security teams.
An analysis of the hardest defensive challenges JavaScript teams face when protecting apps from fully autonomous AI attackers, with practical security implications for modern web stacks.
This article explains how to test application resilience against autonomous AI-driven ransomware, using a real-world attack to highlight practical defensive controls, failure points, and response priorities.
A practical guide for developers on the essential security, reliability, and quality tests to run before integrating an LLM into your product.
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Mozilla’s 0din research shows how AI coding agents like Claude Code can be manipulated through context injection in seemingly clean GitHub repositories to install malware, exposing a new class of developer workflow risk.
The first AI-built zero-day signals a new era of automated attacks that JavaScript frontend teams must address with stronger supply-chain, runtime, and dependency defenses.