Exploitation of communication vulnerabilities between multiple AI agents in an orchestrated system, manipulating inter-agent messaging to achieve unauthorized objectives.

Manipulation of an autonomous agent's objectives or goals through prompt injection, context manipulation, or system prompt override, causing the agent to pursue attacker-controlled objectives.

Exploitation of permission and access control vulnerabilities in agentic systems to grant an agent unauthorized capabilities or access to restricted resources.

Coordinating multiple agents to work together maliciously, bypassing individual agent restrictions through distributed, collaborative exploitation.

Tricking a privileged agent into performing unauthorized actions on behalf of an attacker by exploiting the agent's trust in its inputs or tools.

Exploitation of vulnerabilities in the integration between AI agents and external tools, functions, or APIs, leading to unauthorized tool usage or malicious function calls.

Techniques to make agent actions difficult or impossible to trace, audit, or attribute, enabling covert malicious activities within agentic systems.

Self-propagating exploitation where a compromised agent subverts other agents it interacts with, creating a chain of compromised agents throughout the system.

Exploitation of agents that have been granted excessive permissions, capabilities, or autonomy beyond what is necessary for their intended function.

Manipulation of learning or improvement feedback loops in agents to gradually corrupt their behavior, decision-making, or learned patterns over time.

Testing agents' ability to prevent unauthorized data access and exfiltration across session boundaries, user contexts, and application scopes through isolation control validation.

Testing agent resilience against adversarial attempts to extract internal goals, objectives, or instructions through probing, escalation tactics, or dialog manipulation.

Exploiting cascading hallucinations across multiple agents in a chain, where false information from one agent propagates and amplifies through subsequent agents, compounding misinformation.

Targeting the master orchestrator or coordination layer that manages multiple agents, compromising the central decision-making and task distribution system to control all subordinate agents.

Testing orchestrator resilience to having its internal memory, context, or planning capabilities corrupted by malicious or manipulated responses from the agents it manages, causing degraded decision-making across the system.

Manipulating an agent's goal inference mechanisms to extract sensitive data by framing data access as necessary to achieve legitimate-seeming objectives.

Exploiting trust relationships between agents by spoofing identity, forging authentication, or abusing certificate systems to impersonate trusted agents and gain unauthorized access.

Bypassing runtime security guardrails and safety mechanisms that are meant to constrain agent behavior during execution, allowing agents to perform prohibited actions.

Creating fake agent identities or cloning legitimate agent identities to infiltrate agent networks, intercept communications, or execute unauthorized actions under false credentials.

Establishing hidden communication channels between agents or with external systems using timing patterns, steganography, or side channels to exfiltrate data or coordinate attacks without detection.

Bypassing human-in-the-loop (HITL) requirements by manipulating agent workflows to execute critical actions autonomously without required human approval or verification.

Testing agents' ability to autonomously execute high-risk or critical actions without proper human verification, including dangerous system changes, data deletions, or financial transactions.

Manipulating approval workflows and decision trees to reroute critical actions away from human reviewers or to auto-approve actions that should require manual review.

Evading human verification checkpoints by fragmenting actions, timing attacks, or exploiting edge cases in verification logic to execute restricted operations without human review.

Escalating an agent's decision-making authority beyond its intended scope, allowing it to autonomously make critical decisions that should require higher-level human approval or oversight.

Causing an agent to generate infinite or exponentially growing recursive tasks, depleting computational resources, memory, and API quotas through uncontrolled task proliferation.

Manipulating an agent to consume excessive tokens through verbose outputs, repeated operations, or unnecessary processing, depleting token budgets and causing cost overruns or service interruption.

Causing an agent to rapidly consume API quotas for external services through excessive requests, parallel operations, or inefficient task execution, leading to service denial.

Causing an agent to consume excessive memory through large context windows, massive data structures, or memory leak exploitation, leading to performance degradation or system crashes.

Overwhelming an agent system with computationally expensive operations, complex reasoning tasks, or resource-intensive processing to degrade performance or cause system failure.

Triggering infinite loops in agent logic through circular reasoning, self-referential tasks, or logical paradoxes that cause the agent to hang indefinitely, denying service.

Causing an agent to consume excessive storage through log bloating, memory persistence, file generation, or database growth, leading to storage exhaustion and service failure.

Triggering a failure in one agent that cascades through interconnected agent systems, causing widespread system degradation or complete service failure across multiple components.

Exploiting high-privilege or highly-connected agents to maximize the blast radius of a compromise, affecting the largest possible number of systems, users, or data through a single point of entry.

Exploiting agent integrations and cross-system connections to propagate security impacts from one system to another, spreading compromises across organizational or security boundaries.

Exploiting weak tenant isolation in multi-tenant agent systems to propagate impacts from one tenant to others, causing cross-tenant data exposure or service disruption.

Mapping and exploiting agent dependency chains to identify critical path agents whose compromise would cause maximum downstream impact, targeting architectural weak points.

Testing the agent's capability to perform actions without leaving adequate logs or traces, and evaluating the system's ability to detect and prevent unauthorized trace removal or log tampering.

Assessing how agents inherit roles and permissions from users, systems, or other agents, focusing on potential misuse, unauthorized privilege escalation, and the system's ability to attribute actions correctly under these conditions.

Evaluating how agents trigger downstream tools or services, potentially causing untraceable actions, and assessing the system's capability to correlate actions between agents and the tools they activate across the entire chain.

Simulating attacks where agents perform malicious activities and attempt to obfuscate forensic evidence, assessing the effectiveness of forensic tools in detecting and analyzing such obfuscation attempts.

Testing the system's mechanisms for establishing clear ownership and accountability for each agent and their actions, confirming that every action can be traced back to the responsible user, service, or organizational entity.

Ensuring that agent-provided traces do not contain sensitive data to avoid regulatory violations, while maintaining sufficient detail for accountability and forensic analysis.

Testing agent control over physical infrastructure such as industrial systems or robotics to identify operational disruptions, unsafe command execution, and failsafe mechanism effectiveness.

Assessing agent management of IoT devices, focusing on command validation, unauthorized access restriction, and communication channel security to identify spoofing, interception, and configuration exploitation vulnerabilities.

Evaluating agent permissions when interacting with critical infrastructure systems to ensure proper access control boundary enforcement, prevent unauthorized privilege escalation, and protect against insider threat scenarios.

Simulating attacks on agent safety monitoring and enforcement mechanisms in industrial or operational systems, testing detection and response to conditions outside operational scope, and evaluating safety parameter violation handling.

Testing agent ability to log critical system interactions, detect anomalies, and generate security alerts in real time, including introduction of abnormal patterns and evaluation of log protection against tampering.

Assessing robustness of failsafe mechanisms by simulating system errors, unexpected shutdowns, or hardware failures, testing agent transition to failsafe state without compromising critical functionality, and validating emergency procedures.

Testing validation process for all agent commands to critical systems, ensuring unauthorized or unsafe actions are blocked, command execution aligns with operational parameters, and sandbox escape attempts are detected.