diff --git a/Document/content/tests/AITG-MOD-02_Testing_for_Runtime_Model_Poisoning.md b/Document/content/tests/AITG-MOD-02_Testing_for_Runtime_Model_Poisoning.md
index a84fea4..1bd25ec 100644
--- a/Document/content/tests/AITG-MOD-02_Testing_for_Runtime_Model_Poisoning.md
+++ b/Document/content/tests/AITG-MOD-02_Testing_for_Runtime_Model_Poisoning.md
@@ -38,6 +38,6 @@ This test identifies vulnerabilities associated with runtime model poisoning, wh
   - Tool Link: [River on GitHub](https://github.com/online-ml/river)
 
 ### References
-- OWASP Top 10 for LLM Applications 2025. "LLM04: Data and Model Poisoning." OWASP, 2025. [Link](https://genai.owasp.org/)
+- OWASP Top 10 for LLM Applications 2025. "LLM04: Data and Model Poisoning." OWASP, 2025. [Link](https://genai.owasp.org/llmrisk/llm042025-data-and-model-poisoning/)
 - NIST AI 100-2e2025, "Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations," Section 2.3 "Poisoning Attacks and Mitigations." NIST, March 2025. [Link](https://doi.org/10.6028/NIST.AI.100-2e2025)
 - "Poisoning Attacks on Machine Learning." A. N. Jagielski, et al. [Link](https://arxiv.org/abs/1804.00792)