Universal suffix attack on Jev model
A study finds that one short suffix flips 43% of unseen documents for the Jev model; a suffix from one task flips 90-100% of samples in other tasks, and the attack finds it in minutes. Link
THE JEV GUIDE · CURATED EDITION
Cybersecurity.
Launch news, explanations, demos, and community projects around TypeSafe Jev, organized by topic. Every entry links back to its X source.
Curated selection · Not exhaustive · Updated manually
6757curated posts
3414original videos
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Peekray: Using Jev to Detect Scam Links
The author built Peekray, a tool that lets users paste a suspicious link. In about a second, it follows the link to its final destination, checks it against 164,000+ known scam links, and consults Jev, TypeSafe AI's model, in case it's too new for any list.
Jev Supercharges Auth Logic with Lower Latency
Boaz Foux praises Jev for its blazing speed in replacing traditional auth logic, slashing latency and turning routine security into a frictionless experience.
Givvy Launches Proactive Cyber Defense AI Using Jev Model
Analyzes threats via email screening and open-source search, combines rescanning with quarantine/blocking, and continues rule-based decisions when AI is unavailable.
Can Jev-guard block repo-level hook pre-execution?
A security boundary question: whether a repo's own .mcp.json or hooks can run before trust checks, and whether Jev-guard can intercept early.
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Jev Model Performance in Prompt Injection Detection
In an experiment with 50 prompt injections hidden in 5,000-word articles, Jev and Clef caught all 50 with ≤1 false flag, while Horizon Guard flagged 46/50.
Prompt-Injection Classifier Comparison: Jev Misses Cluster in Technical Obfuscation
Across 800 prompts, different prompt-injection classifiers fail on different attack types. Jev misses cluster in technical obfuscation, Clef in social engineering, and Wolf's in linguistic tricks and context manipulation. Horizon Guard misses only 5 (but...).
Claude + Jev Vehicle Sweep Finds Suspicious Signals
Before buying a car, the author ran a sweep on the vehicle. With the engine off and phone in airplane mode, Claude listed every signal in the cabin and Jev made one call, uncovering 3 things that shouldn't be there.
Sentry uses Jev to screen 10M events daily for prompt injection
Per the post, Sentry uses Jev to check 10M events daily for prompt injection, spending $263 per day, and is testing its own classifier aiming for 90% cost reduction. Highlights the risk of prompt injection via error reports for coding agents.
Sentry spends $263/day using Jev to detect prompt injection
Cloudflare Developers highlights Sentry using Jev to screen error reports for prompt injection, checking 10M events daily for $263; the team is testing its own classifier to match Jev's accuracy for 90% less.
Eryma: An LLM Security Project Using Jev
This project focuses on LLM security, using a modern decision model like Jev as a buffer layer and testing it with Garak, achieving a 98.86% improvement in detection hits.
Use Jev to detect hacking on all access and prevent leaks
A discussion about using Jev to judge hacking attempts on all access in order to prevent information leaks.
