Exploring the limits, opportunities, and risks of generative AI through a wild experiment
Veracode’s 2026 GenAI Code Security Report reveals AI-generated code still lags on security, with 44% of outputs introducing vulnerabilities.
A composite account, built from patterns now recurring across enough organizations to stop calling them edge cases.
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.
AI is smart, but smart doesn’t mean trustworthy.
Opus 5 rivals Fable at half the cost—which one wins?
HAL reviews ash120’s quantum COBOL paper with sharp wit, exposing why packed decimals, entanglement keys, and quiet rounding can’t hold quantum truth.
An in-depth exploration of the defensive AI technique turning hackers’ own methods against them.
Mistral’s take on AI regulation: balancing open innovation, safety, transparency, and accountability without stifling open-source model development.
A balanced look at whether social platforms and AI companies should be liable for illegal content, with child safety, free speech, and fair oversight in focus.
Should tech companies and AI builders be liable for illegal content? A balanced look at platform duty, generative AI risks, and accountability.
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.
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