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PuzzleMask: Abusing Plain Prose as a Covert AI Attack Vector

Check Point details PuzzleMask, a plain-prose technique that bypasses LLM gatekeeper policy checks, letting hidden payloads reach target models unreviewed.

Check Point Research describes PuzzleMask, a prompt-crafting technique that hides policy-violating payloads inside plain-English prose wrappers, bypassing quick LLM-based policy checks without emojis, Base64, or invisible formatting. The researchers tested 23 automated prompts against gatekeepers including GPT-4o-mini, GPT-OSS-Safeguard 20b, Claude 3 Haiku, and Llama Guard 3, and all were classified as safe despite policies that flagged the plain versions. When submitted to GPT-5 in thinking-high mode with a Python interpreter, the target model extracted and acted on the payload in over 90% of trials. The technique is not itself a jailbreak but can carry a jailbreak prompt as payload; mitigations include input paraphrasing, hardened gatekeeper policies, and output monitoring.

Check Point Researchupdated · 5d agofirst · 6d agoAI safety & security 2 sources

Hackers Can Hide Malicious AI Commands Inside Normal English to Bypass Security Filters

Check Point's PuzzleMask technique hides malicious prompts in ordinary English that fast gatekeeper models miss but high-reasoning downstream models execute.

Check Point researchers disclosed PuzzleMask, a technique concealing policy-breaking instructions in natural-language prose without encodings or invisible characters. Fast screening models classified all 23 crafted wrappers as safe, while a high-reasoning model recovered and acted on the hidden instruction in 17 of 18 tests (94.4%). The gap stems from capability imbalance between gatekeeper and target models, with defenses including paraphrasing untrusted input, stricter self-referential wording rules, and output/tool-call monitoring.

Cyber Security News · 5d agoAI safety & security1

Muse can shop, write emails, and negotiate prices for users, all through WhatsApp

Meta launched Muse, a WhatsApp-controlled agent running on an isolated VM with a Sentinel gatekeeper, able to shop, email, book travel, and negotiate.

Meta introduced Muse, an autonomous agent controlled through WhatsApp that runs on its own cloud virtual machine, plans multi-step tasks, browses, fills forms, and negotiates on users' behalf. Payments run through Stripe's Link using one-time cards, which Meta calls the first AI agent covered by Link's purchase protection, with Shop Pay and 1Password integration planned. A second agent, Sentinel, gates all Muse network access and holds credentials, and a Muse Confidential VM with user-held encryption keys is planned later this year. Muse's model reportedly scored 44-48 on Artificial Analysis Intelligence Index v4.3, up from 31 for Muse Spark in April, near GPT-5.6 Sol's 47; it launches first in the US on iOS and Android.

The Decoderupdated · 4d agofirst · 6d agoAI industry 11 sources1

[AINews] AEF-1 standard emerges for Third Party Evaluators, as Xai, OpenAI, and Anthropic all cosign

xAI, OpenAI, and Anthropic cosign the AEF-1 third-party evaluation standard while Dario Amodei proposes embedded evaluators for safety verification.

The AI Evaluator Forum published AEF-1, a baseline standard for independent third-party AI evaluations covering access, conflicts of interest, funding relationships, recusal, and transparency, cosigned by xAI, OpenAI, and Anthropic. Dario Amodei wrote a rare personal blogpost proposing embedded evaluators such as METR with desks, badges, company laptops, and internal-risk-team-level access to verify safety commitments, plus democratic and global coordination frameworks. The roundup also covers the pacing debate: Bilal Chughtai left Google DeepMind arguing progress may outrun alignment, while critics including Aidan Gomez and Cohere push back against slowdowns and lab gatekeeping. Additional items include Cline Desktop's launch with open-weight model support.

Latent Space · 1d agoAI safety & security

Who gets to define the rules for AI?

Cohere CEO Aidan Gomez attacks big-lab antitrust exemption proposals as cartel behavior that lets incumbents write AI safety rules.

Cohere CEO Aidan Gomez argues that proposals from large AI labs—particularly Anthropic's roadmap requesting antitrust exemptions for safety coordination—amount to a cartel letting incumbents define rules for everyone else. He draws parallels to the 1975 SEC NRSRO credit-rating designations and the EU's 1985 Motor Vehicle Block Exemption, where safety justifications produced incumbent-protecting market structures. Gomez supports independent review of highly capable AI systems but disputes who writes the standards, who conducts review, and who participates. He also warns AI cyber offense is getting cheaper faster than defenses are improving.

Hacker News · AI · 2d agoAI policyHN 41↑ · 29 comments

The Rise of the Forward Deployed Engineer — and How To Do the Job Right

Palantir veteran Vinoo Ganesh traces the forward deployed engineer role and shares practices for building effective FDE teams.

Kepler CEO and former Palantir forward deployed engineer Vinoo Ganesh argues that labs, startups, and PE firms hire FDEs without a shared definition of the role. He recounts Palantir's Project Frontline rotation, which trained about 250 software engineers as FDEs, many now leading forward deployed teams at OpenAI, Anthropic, xAI, and Anduril. A 2013 failure of the Phoenix transaction store at a bank, where real-world data gaps caused roughly 2.3 million keyspaces and an out-of-memory crash, illustrates why FDEs must own the gap between design and production reality. At Kepler he places the FDE function inside product rather than sales.

Latent Space · 4d agoAI industry 4 sources1

AWS limits AI agents’ data access, even when manipulated

AWS detailed propagating user authorization context through Bedrock AgentCore so downstream services enforce access controls even if the agent is manipulated via prompt injection.

AWS described an architecture for Amazon Bedrock AgentCore where user tokens and department claims are validated at runtime and propagated to DynamoDB, Bedrock Knowledge Bases, and Salesforce. Downstream services enforce authorization themselves, so a prompt-injected or buggy agent cannot retrieve data the user is not entitled to see. AWS demonstrated the pattern with a CRM use case separating Sales and Finance access and recommends IAM-backed knowledge bases for stricter isolation.

Help Net Security · 28d agoAI safety & security