Current Volume 9
AI-Assisted Vulnerability Discovery and Reporting: Reliability Challenges, Security Risks, and Future Directions
Abstract
In the contemporary world of cyber security, AI plays a significant part and is extensively recognized in finding and reporting vulnerabilities. Due to recent advancement in Machine Learning (ML), Deep Learning (DL) and Large Language Models (LLMs), various automated tools for finding vulnerabilities in software, reporting security bugs, and suggest patches for them are currently available. This work aims at identifying existing literature on AI assisted vulnerability detection and reporting system with a special focus on their security and reliability issue. Works from year 2023 to 2026 are reviewed and analyzed with categorizing them on the basis of their aim, techniques employed, merits and demerits. From our analysis, key reliability issues identified are; false positives, false negatives, hallucinations, inaccurate severity rating, and complexity in interpretations whereas the major security threats encountered were prompt injection attacks, adversarial manipulation of input data, poisoning data and leaking sensitive information. Based on the findings of this study, it is concluded that while there are numerous benefits to the AI assisted cyber security system, humans can never be out of the loop and supervision and interpretation of security flaws based on credibility cannot be disregarded in practical applications. We highlight some major challenges in current approaches along with several future research direction in order to achieve a dependable and secure AI-assisted vulnerability assessment system.
Keywords
Artificial Intelligence, Cyber Security, Vulnerability Discovery, Vulnerability Reporting, Trustworthy AI, Large Language Models.
Citations
IRE Journals:
Shaik Mohammad Yasin, Kalisetti Venkatesh, Heema Chetri "AI-Assisted Vulnerability Discovery and Reporting: Reliability Challenges, Security Risks, and Future Directions" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 4779-4787 https://doi.org/10.64388/IREV9I11-1718467
IEEE:
Shaik Mohammad Yasin, Kalisetti Venkatesh, Heema Chetri
"AI-Assisted Vulnerability Discovery and Reporting: Reliability Challenges, Security Risks, and Future Directions" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1718467
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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