Mining Threat Intelligence about Open-Source Projects and Libraries from Code Repository Issues and Bug Reports
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Abstract (arXiv)
Open-Source Projects and Libraries are being used in software development while also bearing multiple security vulnerabilities. This use of third party ecosystem creates a new kind of attack surface for a product in development. An intelligent attacker can attack a product by exploiting one of the vulnerabilities present in linked projects and libraries. In this paper, we mine threat intelligence about open source projects and libraries from bugs and issues reported on public code repositories. We also track library and project dependencies for installed software on a client machine. We represent and store this threat intelligence, along with the software dependencies in a security knowledge graph. Security analysts and developers can then query and receive alerts from the knowledge graph if any threat intelligence is found about linked libraries and projects, utilized in their products.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Aug 2018.
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Citing papers per year: 2021: 3; 2022: 1; 2023: 1; 2024: 0; 2025: 1.
6 papers.
- 2021Generating Fake Cyber Threat Intelligence Using Transformer-Based Modelscited by 29
- 2021What are the attackers doing now? Automating cyber threat intelligence extraction from text on pace with the changing threat landscape: A surveycited by 14
- 2022Towards Automated Classification of Attackers' TTPs by combining NLP with ML Techniquescited by 5
- 2025False Alarms, Real Damage: Adversarial Attacks Using LLM-based Models on Text-based Cyber Threat Intelligence Systemscited by 2
- 2023AI Security Threats against Pervasive Robotic Systems: A Course for Next Generation Cybersecurity Workforcecited by 1
- 2021Knowledge mining of unstructured information: application to cyber-domaincited by 0
- 2025False Alarms, Real Damage: Adversarial Attacks Using LLM-based Models on Text-based Cyber Threat Intelligence Systems5 Jul 2025
- 2023AI Security Threats against Pervasive Robotic Systems: A Course for Next Generation Cybersecurity Workforce15 Feb 2023
- 2022Towards Automated Classification of Attackers' TTPs by combining NLP with ML Techniques18 Jul 2022
- 2021What are the attackers doing now? Automating cyber threat intelligence extraction from text on pace with the changing threat landscape: A survey14 Sep 2021
- 2021Knowledge mining of unstructured information: application to cyber-domain8 Sep 2021
- 2021Generating Fake Cyber Threat Intelligence Using Transformer-Based Models8 Feb 2021