AI Security Insights

Threat Research

Our own security models and the attack techniques behind them: benchmarks, training decisions and new classes of AI-driven malware.

9 articles

Detecting risky shell commands

An expanded linear classifier provides the most robust combination of detection and low false-positive rates in our ShellRisk experiments. Full chunking helps the encoder on long scripts, but does not resolve calibration or weaknesses under comment padding.

Threat Research · Oct 7, 2026 · 16 min · Read →

Lakera vs. Patronus: Comparing prompt injection detection

Lakera vs. Patronus and PromptGuard vs. Patronus on 825 shared inputs: Patronus produced fewer false positives, while Lakera detected more attacks in selected agent benchmark texts.

Threat Research · Sep 27, 2026 · 7 min · Read →

Wolf Defender on the Buried Injections benchmark

Wolf Defender Small v2 detects 524 of 629 embedded attacks with one false positive. Two internal candidates detect 628 and 629. What matters is what the benchmark actually tests.

Threat Research · Sep 25, 2026 · 4 min · Read →

Wolf Defender v2: prompt injection detection that runs on the laptop

Wolf Defender v2 detects prompt injection and jailbreaks in German and English, with a 2,048-token context, on a laptop CPU. The biggest change since v1: far fewer false positives on hard benign text.

Threat Research · Sep 7, 2026 · 8 min · Read →

Our AI-Security Model Zoo Is Now Open Source

Threat Research · Jul 21, 2026 · 7 min · Read →

Orca-Sonar: Our Multilingual Document Classifier for AI Security

We're releasing Orca-Sonar, a fast, multilingual model (German + English) that sorts text into 7 topic classes. It's part of the Patronus Protect stack and routes incoming content by topic and sensitivity before it reaches an LLM, a DLP gate, or a storage tier.

Threat Research · Jun 12, 2026 · 8 min · Read →

When Malware Starts to Think: Why AI-Driven Worms Require a New Security Layer

A new research paper shows how AI agents can turn traditional computer worms into adaptive, self-replicating attack systems. Instead of following a fixed exploit chain, these worms can reason, use tools, learn from failed attempts, and spread across networks by using compromised compute. This shift makes AI runtime security essential, and shows why Patronus Protect is built for the next generation of AI-driven malware.

Threat Research · Jun 9, 2026 · 6 min · Read →

New AI-Security Model: Wolf Defender

Threat Research · Apr 15, 2026 · 3 min · Read →

Today we’re releasing our first security model: Wolf Defender

Threat Research · Mar 18, 2026 · 5 min · Read →

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