Red teaming LLMs exposes a harsh truth about the AI security arms race
Unrelenting, persistent attacks on frontier models make them fail, with the patterns of failure varying by model and developer. Red teaming shows that it’s not the sophisticated, complex attacks that can bring a model down; it’s the attacker automating continuous, random attempts that will inevitably force a model to fail.That’s the harsh truth that AI apps and platform builders need to plan for as they build each new release of their products. Betting an entire build-out on a frontier model prone to red team failures due to persistency alone is like building a house on sand. Even with red teaming, frontier LLMs, including those with open weights, are lagging behind adversarial and weaponized AI.The arms race has already startedCybercrime costs reached $9.5 trillion in 2024 and forec [...]
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Anthropic vs. OpenAI red teaming methods reveal different security priorities for enterprise AI
Model providers want to prove the security and robustness of their models, releasing system cards and conducting red-team exercises with each new release. But it can be difficult for enterprises to pa [...]
Prompt Security's Itamar Golan on why generative AI security requires building a category, not a feature
VentureBeat recently sat down (virtually) with Itamar Golan, co-founder and CEO of Prompt Security, to chat through the GenAI security challenges organizations of all sizes face. We talked about shado [...]
OpenAI admits prompt injection is here to stay as enterprises lag on defenses
It's refreshing when a leading AI company states the obvious. In a detailed post on hardening ChatGPT Atlas against prompt injection, OpenAI acknowledged what security practitioners have known fo [...]
Every leading AI agent failed at least one security test during a massive red teaming competition
A major red teaming study has uncovered critical security flaws in today's AI agents. Every system tested from leading AI labs failed to uphold its own security guidelines under attack.<br /&g [...]
Mythos autonomously exploited vulnerabilities that survived 27 years of human review. Security teams need a new detection playbook
A 27-year-old bug sat inside OpenBSD’s TCP stack while auditors reviewed the code, fuzzers ran against it, and the operating system earned its reputation as one of the most security-hardened platfor [...]
Anthropic's Claude Code Security is available now after finding 500+ vulnerabilities: how security leaders should respond
Anthropic pointed its most advanced AI model, Claude Opus 4.6, at production open-source codebases and found a plethora of security holes: more than 500 high-severity vulnerabilities that had survived [...]
Anthropic published the prompt injection failure rates that enterprise security teams have been asking every vendor for
Run a prompt injection attack against Claude Opus 4.6 in a constrained coding environment, and it fails every time, 0% success rate across 200 attempts, no safeguards needed. Move that same attack to [...]