mlsanityData to 7 Oct 2026

RECEIPT: Deterministic, Reward-Hacking-Resistant Verification for White-Box Agentic XSS Discovery

arXiv 2607.18575 ↗First posted 20 Jul 2026cs.CRcited by 1

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

Cross-Site Scripting (XSS) remains one of the most prevalent and damaging classes of web vulnerabilities. LLM-based coding agents offer a promising approach to XSS discovery by combining source-code reasoning with interactive testing against a running application. However, a coding agent's claims cannot be trusted on their own. We characterize three reward-hacking behaviors in white-box agentic XSS discovery and propose three requirements that an ideal verifier should meet. We present RECEIPT, a verification framework that makes agent-reported XSS findings trustworthy by enforcing environment isolation, PoC constraints, role separation, and verdict binding. Each confirmation therefore establishes two properties: the script runs in a real browser, and the payload was planted under the attacker role and executed in the victim role's browser. This constrained replay procedure makes validation deterministic and reproducible. We evaluate RECEIPT on 95 real-world web-application targets drawn from popular open-source projects. Within a 20 per-application budget, RECEIPT found 24 previously unknown XSS vulnerabilities, 12 of which have already been acknowledged by maintainers after responsible disclosure, and recovered the labeled CVE in 36% of known-vulnerability recovery targets. Compared with the same agent using self-judgment and with black-box scanners, RECEIPT confirms more real exploits while admitting no false positives.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 20 of its 59 references that are in the map. First posted on arXiv 20 Jul 2026.

Builds on

20 of 59 references.

Closest ancestors · 6

Same direction, newest first

  1. 2026Revelio: Cost-Efficient Agentic Memory Safety Vulnerability Detection For Repository-Scale Codebases20 Jun
  2. 2025CVE-Bench: A Benchmark for AI Agents' Ability to Exploit Real-World Web Application Vulnerabilities21 Mar
  3. 2024EnIGMA: Interactive Tools Substantially Assist LM Agents in Finding Security Vulnerabilities24 Sep
  4. 2024Teams of LLM Agents can Exploit Zero-Day Vulnerabilities2 Jun
  5. 2024LLM Agents can Autonomously Exploit One-day Vulnerabilities11 Apr
  6. 2024LLM Agents can Autonomously Hack Websites6 Feb

Other references · 14

  1. 2024SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineeringcited by 1,628
  2. 2024LLM Evaluators Recognize and Favor Their Own Generationscited by 651
  3. 2025Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscationcited by 338
  4. 2022Defining and Characterizing Reward Hackingcited by 184
  5. 2024Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Modelscited by 156
  6. 2025Natural Emergent Misalignment from Reward Hacking in Production RLcited by 111
  7. 2024IRIS: LLM-Assisted Static Analysis for Detecting Security Vulnerabilitiescited by 100
  8. 2023LLMs Cannot Reliably Identify and Reason About Security Vulnerabilities (Yet?): A Comprehensive Evaluation, Framework, and Benchmarkscited by 94
  9. 2025Establishing Best Practices for Building Rigorous Agentic Benchmarkscited by 94
  10. 2024NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Securitycited by 90
  11. 2025CyberGym: Evaluating AI Agents' Real-World Cybersecurity Capabilities at Scalecited by 71
  12. 2023GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysiscited by 65
2 more
  1. 2022Twenty-two years since revealing cross-site scripting attacks: a systematic mapping and a comprehensive surveycited by 2
  2. 2025Dancer in the Dark: Synthesizing and Evaluating Polyglots for Blind Cross-Site Scriptingcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

  1. 2026Cheap to Hypothesize, Costly to Verify: The Defense Surface of Agentic Vulnerability Discovery
  2. 2024ST-WebAgentBench: A Benchmark for Evaluating Safety and Trustworthiness in Web Agents
  3. 2026Prismata: Confining Cross-Site Prompt Injection in Web Agents
  4. 2026Agent Flight Recorder: Tamper-Evident Audit Trails with On-Chain Anchoring for Long-Horizon Tool-Using Agents
  5. 2026AWE: Adaptive Agents for Dynamic Web Penetration Testing
  6. 2026WebMCP-Phalanx: Enforcing and Characterizing Trust Boundaries for Browser-Integrated LLM Agents
  7. 2025Fortifying the Agentic Web: A Unified Zero-Trust Architecture Against Logic-layer Threats
  8. 2026Tencent WorkBuddy Bench: A Multi-Domain Coding-Agent Benchmark with Contamination-Resistant Task Construction