AI & LLMs Show Promise in Squashing Software Bugs
Large language models (LLMs) can help app security firms find and fix software vulnerabilities. Malicious actors are on to them too, but here's why defenders may retain the edge.
Vulnerabilities are flaws attackers can exploit to access systems or data; timely patching, isolation, and least privilege reduce the impact.
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Background for this topic.
A vulnerability is a weakness in a system’s design, code, configuration, or operating process that could allow an attacker to violate a security requirement. It may affect software, hardware, networks, cloud services, or exposed interfaces, and is not automatically exploitable: practical risk depends on factors such as exposure, required privileges, available attack paths, and existing controls. Outcomes can include unauthorized access, information disclosure, code execution, or disruption of service.
Effective vulnerability management combines accurate asset inventory with code review, security testing, scanning, and trusted vulnerability intelligence. Organizations should prioritize weaknesses affecting reachable, business-critical systems—especially when exploitation is known or requires little access—then patch or otherwise mitigate them and verify the fix. Where patching is delayed, controls such as disabling an exposed feature, restricting network access, or strengthening authentication can reduce the attack surface. Records should preserve affected versions, risk decisions, remediation owners, and validation results.
Large language models (LLMs) can help app security firms find and fix software vulnerabilities. Malicious actors are on to them too, but here's why defenders may retain the edge.
Though Cisco reports of no known malicious exploitation attempts, three of its wireless access points are vulnerable to these attacks.
A research tool by the company found a vulnerability in the SQLite open source database, demonstrating the "defensive potential" for using LLMs to find vulnerabilities in applications before they're publicly released.