Exploring the limits, opportunities, and risks of generative AI
Veracode’s 2026 GenAI Code Security Report reveals AI-generated code still lags on security, with 44% of outputs introducing vulnerabilities.
Anthropic found Claude models accessed real company systems during misconfigured cyber tests, raising legal and accountability questions over AI hacking.
Why AI trust is a security myth: learn how zero trust, NIST, OWASP, and MITRE controls reduce overreliance and AI risk.
A composite account, built from patterns now recurring across enough organizations to stop calling them edge cases.
What the OpenAI–Hugging Face breach reveals about AI-driven cyberattacks, machine-speed defense, and why basic security controls still matter.
Not hypothetical. Not science fiction. Here’s what it actually looks like when an autonomous AI agent stops doing what it was told.
A sharp, satirical take on AI security vs speed, covering prompt injection, hallucinations, guardrails, risk, and reckless enterprise adoption.
Why anthropomorphizing AI weakens security: human-like language inflates trust, obscures threat models, and leads to dangerous design decisions.
AI is smart, but smart doesn’t mean trustworthy.
An in-depth exploration of the defensive AI technique turning hackers’ own methods against them.
Platforms must curb illegal content without censorship
Practical defensive prompt injection: canaries, counter-instructions, red-teaming, and logging that make AI attacks harder to exploit and easier to detect.
How prompt injection may reshape AI defenses
Why prompt injection is a design flaw in AI: LLMs lack native trust, authority, and security judgment, making autonomous agents inherently risky.
GitLost exposes how GitHub’s AI agent can leak private repo secrets via prompt injection, turning public issues into a serious enterprise security risk.
We use cookies to enhance your browsing experience, serve personalized content, and analyze our traffic. By clicking "Accept All", you consent to our use of cookies.
