AI Agent Goal Hijacking Defense

We deliver a detailed inventory of all potential attack vectors specific to your agent's architecture, including tool misuse, memory corruption, and external API manipulation. This actionable map prioritizes remediation based on exploit likelihood and business impact.

Implementation of runtime monitoring and guardrails that detect and block attempts to subvert the agent's primary objectives. This includes cryptographic verification of critical instructions and anomaly detection in task execution sequences.

Hardening of the agent's tool-calling framework with strict input validation, output sanitization, and permission scoping. We eliminate unsafe tool chaining and enforce least-privilege access to databases and external services.

A detailed report documenting successful and blocked attacks from our red team engagement, using frameworks like MITRE ATLAS. Includes proof-of-concept exploits and step-by-step remediation guidance for your engineering team.

Deployment of lightweight, production-ready sensors that feed security telemetry into your existing SIEM or SOAR platform (e.g., Splunk, Datadog). Enables real-time detection of novel attack patterns post-deployment.

Hands-on workshops for your AI and engineering teams on secure agent design patterns, common vulnerability pitfalls, and how to interpret and respond to security alerts from the deployed monitoring system.

Protect algorithmic trading and autonomous procurement agents from adversarial manipulation that could trigger market volatility or execute unauthorized transactions. Our defense strategies are informed by real-world red teaming of B2B AI agent exchanges and smart contract negotiation platforms.

Secure ambient AI documentation tools and diagnostic agents against goal hijacking that could alter treatment recommendations or corrupt patient records. We apply rigorous testing frameworks aligned with healthcare AI compliance standards.

Harden the decision-making logic of autonomous warehouse robots, drones, and manufacturing arms to prevent adversaries from subverting safety protocols or inducing harmful physical actions. Our testing integrates learnings from Physical AI and Robotics Security Red Teaming.

Fortify collaborative AI networks used for geospatial intelligence, secure communications, and autonomous systems in contested environments. We implement defense-in-depth architectures resistant to sophisticated persistent threats.

Secure autonomous replenishment agents and digital supply chain twins against manipulation that could disrupt global logistics, corrupt inventory data, or induce catastrophic replenishment failures.

Defend agentic workflows and custom enterprise copilots from prompt injection and tool corruption attacks that could lead to data exfiltration, compliance violations, or unauthorized system access. Our approach is informed by continuous testing of complex, multi-step AI workflows.