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AI Security

Articles on AI agent security, adversarial testing, posture management, and enterprise AI risk.

Techy cover for the Humanbound Agent Attack Scenario Library, showing a test_pack.yaml code card that maps an agent failure to an OWASP Agentic category and the guardrail that closes it, with Agent Goal Hijack, Tool Misuse, and Memory Poisoning tags.
AI Security
Sep 3, 2026

Beyond AI Security: The Rise of AI SecOps: Splunk + Humanbound

Splunk is where most SOCs already live. Here's how Humanbound streams AI agent security findings into Splunk as structured, HMAC-signed webhooks, so agent security gets the same real-time alerting and incident response as everything else the SOC already handles.

SASofia Aliferi
Techy cover for the Humanbound Agent Attack Scenario Library, showing a test_pack.yaml code card that maps an agent failure to an OWASP Agentic category and the guardrail that closes it, with Agent Goal Hijack, Tool Misuse, and Memory Poisoning tags.
AI Security
Sep 3, 2026

Beyond AI Security: The Rise of AI SecOps: Microsoft PyRIT + Humanbound

PyRIT is Microsoft's open-source, research-grade red teaming framework. Here's how a point-in-time PyRIT engagement and Humanbound's continuous, compliance-mapped monitoring plug into each other, including how PyRIT's findings can train the Humanbound Firewall directly.

SASofia Aliferi
Techy cover for the Humanbound Agent Attack Scenario Library, showing a test_pack.yaml code card that maps an agent failure to an OWASP Agentic category and the guardrail that closes it, with Agent Goal Hijack, Tool Misuse, and Memory Poisoning tags.
AI Security
Sep 3, 2026

Beyond AI Security: The Rise of AI SecOps: Promptfoo + Humanbound

Promptfoo and Humanbound aren't competing for the same slot. Here's how Promptfoo's CI red teaming and Humanbound's continuous, compliance-mapped monitoring plug into each other, including how Promptfoo's scan results can train the Humanbound Firewall directly.

SASofia Aliferi
Techy cover for the Humanbound Agent Attack Scenario Library, showing a test_pack.yaml code card that maps an agent failure to an OWASP Agentic category and the guardrail that closes it, with Agent Goal Hijack, Tool Misuse, and Memory Poisoning tags.
AI Security
Aug 31, 2026

Agent Security Debt: Nobody Is Trying to Break Your AI Agent until It Ships

In 2017 I got a CVE for an unencrypted smart bulb. Nine years later, AI agents are shipping with the same gap: nobody tried to break them before launch. Here's how to break your own agent this afternoon, before someone else does.

APAyan Pahwa
Techy cover for the Humanbound Agent Attack Scenario Library, showing a test_pack.yaml code card that maps an agent failure to an OWASP Agentic category and the guardrail that closes it, with Agent Goal Hijack, Tool Misuse, and Memory Poisoning tags.
AI Security
Aug 20, 2026

The Agent Attack Scenario Library: A Community Reference, Mapped to OWASP

A community library of agent attack scenarios, each mapped to the OWASP Top 10 for Agentic Applications and paired with the guardrail that closes it. Open, credited, and free to contribute to.

SASofia Aliferi
Infographic titled 'The Humanbound Firewall: A Multi-Tier Defense for AI Agents' on a dark chalkboard-style background with white and orange text. The layout is divided into five sections. Top-left, 'Why Single-Layer Guardrails Fail' highlights three problems: The Context Gap, Multi-turn Blindness, and The Novelty Lag, each with hand-drawn icons. Below it, 'The 4-Tier Defensive Stack' shows a layered pyramid diagram with four tiers: Tier 0 (Sanitization), Tier 1 (Generic Attack Detection using ensemble detectors like DeBERTa), Tier 2 (Domain-Specific Classifiers with normal traffic and adversarial pattern models plus a streaming LLM), and Tier 3 (The LLM Judge). Arrows show data flowing upward through the tiers. Top-right, 'The Continuous Test-and-Defend Loop' illustrates a cycle where the humanbound CLI/SDK engine runs adversarial tests producing transcripts, which become labeled training data. Below it, 'The Feedback Loop' shows how that data refreshes the Tier 2 classifier inside humanbound-firewall, which protects the live agent in production. Bottom-right, 'Open Source vs. Managed Platform' contrasts the Apache-2.0 licensed open-source firewall (offering transparency and auditability) with the managed platform for CISOs (providing continuous testing, posture scoring, compliance evidence, and cross-deployment intelligence). A NotebookLM logo appears in the bottom-right corner.
AI Security
May 11, 2026

Why we open-sourced humanbound-firewall

We released humanbound-firewall under Apache-2.0. A multi-tier runtime defense for AI agents, with each layer inspectable, escalating on uncertainty, and trainable on your own adversarial test data.

DGDemetris Gerogiannis