SuperClaw, an open-source pre-deployment security testing framework designed especially for autonomous AI coding agents, was released by Superagentic AI. SuperClaw, which was unveiled in late 2025, tackles a growing blind spot in the adoption of enterprise AI: agents are frequently deployed with high privileges and extensive tool access, but the majority of organizations completely neglect structured security validation prior to going live. The fundamental issue that motivated SuperClaw's creation is simple.

Autonomous AI agents challenge the presumptions of all conventional security scanners designed for static, deterministic software by reasoning dynamically over time, making decisions based on accumulated context, and adapting their behavior. SuperClaw is designed to test an agent's behavior in hostile environments, not just its configuration. How SuperClaw Operates: In controlled environments, SuperClaw conducts scenario-driven, behavior-first security assessments against actual agents.

Using its built-in Bloom scenario engine, it creates adversarial scenarios, runs them against a real or simulated agent target, records all evidence, including tool calls and output artifacts, and then evaluates the outcomes against explicit behavior contracts structured specifications that specify each security property's intent, success criteria, and mitigation recommendations. Prompt injection (direct and indirect), encoding obfuscation (Base64, hex, Unicode, typoglycemia), jailbreaks (DAN, role-play, grandmother bypasses), tool-policy bypass via alias confusion, and multi-turn escalation across conversation turns are the five fundamental attack techniques that the framework supports by default. The security behaviors being assessed include medium-severity problems like configuration drift detection and ACP protocol security, high-severity issues like tool-policy enforcement and cross-session boundary integrity, and critical risks like prompt-injection resistance and sandbox isolation.

Method of attack An explanation It tests the prompt-injection of agents. Malicious prompts attempt to take control of the agent's decision-making by overriding developer or system instructions. if the agent is able to recognize and reject injected instructions rather than obeying prompts from content sources or untrusted users.

Genai. Encoding conceals malicious intent within seemingly innocent text by using Base64, hex, Unicode tricks, or typoglycemia-style obfuscation. if encoded payloads can be recognized and rejected by the agent (and its filters) rather than being decoded and executed or forwarded mindlessly. jailbreak methods that get around guardrails, like role-playing, emotional pressure, DAN-style prompts, or "ignore previous rules" patterns.

The agent's ability to withstand attempts to circumvent its content filters and refusal policies.

Tool-bypass causes the agent to call powerful tools in unexpected ways by taking advantage of tool aliases, unclear descriptions, or lax policies. whether the agent can withstand being duped into using risky tools and whether it adheres to stringent allow/deny rules for tools. multi-turn Gradual, multi-step conversations that progress over multiple turns from innocuous inquiries to malevolent goals.

How the agent maintains safety over time rather than just per message, handles long-context interactions, and retains previous instructions. Reports are produced in SARIF format for direct integration with CI/CD workflows and GitHub Code Scanning, HTML for human review, or JSON for automation pipelines. Additionally, SuperClaw combines security and optimization evaluations into a single pipeline by integrating with CodeOptiX, Superagentic AI's multi-modal code evaluation engine. Strict guardrails are built into SuperClaw ships.

It blocks any remote targets by default, preventing accidental or unauthorized use. A working SUPERCLAW_AUTH_TOKEN password that was acquired from the target system's administrator is necessary in order to connect to remote agents. Additionally, the project emphasizes that automated results are signals to be manually verified rather than evidence of exploitation, and it expressly requires written authorization before any test is conducted.

SuperClaw can be installed using pip install superclaw and is currently accessible on GitHub under the Apache 2.0 license. It targets development teams that require production-grade agent security prior to deployment and is a component of the larger Superagentic AI ecosystem, which also includes SuperQE and CodeOptiX. For daily cybersecurity updates, check out X and LinkedIn. To have your stories featured, get in touch with us.