Pith. sign in

REVIEW 2 cited by

Prompt-Enhanced Software Vulnerability Detection Using ChatGPT

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2308.12697 v2 pith:QQ6EMP4L submitted 2023-08-24 cs.SE

Chenyuan Zhang , Hao Liu , Jiutian Zeng , Kejing Yang , Yuhong Li , Hui Li This is my paper
classification cs.SE
keywords vulnerabilitydetectionchatgptpromptsoftwaredesignconsiderllms
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

With the increase in software vulnerabilities that cause significant economic and social losses, automatic vulnerability detection has become essential in software development and maintenance. Recently, large language models (LLMs) like GPT have received considerable attention due to their stunning intelligence, and some studies consider using ChatGPT for vulnerability detection. However, they do not fully consider the characteristics of LLMs, since their designed questions to ChatGPT are simple without a specific prompt design tailored for vulnerability detection. This paper launches a study on the performance of software vulnerability detection using ChatGPT with different prompt designs. Firstly, we complement previous work by applying various improvements to the basic prompt. Moreover, we incorporate structural and sequential auxiliary information to improve the prompt design. Besides, we leverage ChatGPT's ability of memorizing multi-round dialogue to design suitable prompts for vulnerability detection. We conduct extensive experiments on two vulnerability datasets to demonstrate the effectiveness of prompt-enhanced vulnerability detection using ChatGPT. We also analyze the merit and demerit of using ChatGPT for vulnerability detection. Repository: https://github.com/KDEGroup/LLMVulnerabilityDetection.

Discussion (0). Sign in to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Evaluating Large Language Models for Symbolic Security Protocol Analysis

    cs.CR 2026-07 accept novelty 6.0 of 10

    On 130 obfuscated security protocols, GPT and DeepSeek verdicts are no substitute for ProVerif/OFMC: chat models over-alarm, reasoning models miss about half of true attacks, and confidence scores cannot distinguish c...

  2. Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques

    cs.CR 2025-07 conditional novelty 4.0 of 10

    A survey that maps LLM applications, vulnerabilities, and defenses across eight cybersecurity domains, but with significant citation and rigor problems.

Pith tools