The Complexities of Dependency Vulnerabilities: A Deep Dive into the 2024 Dependency Management Report
Dealing with dependency vulnerabilities in software projects can often lead to unexpected breakages, as a recent report has uncovered. According to the 2024 Dependency Management Report by Endor Labs, patches deployed for dependency vulnerabilities result in breakages 75% of the time. Minor updates have an even higher breakage rate of 94%, while version upgrades top the chart at 95%.
Software dependencies, the external code or libraries that projects rely on, pose significant challenges during application development. Addressing vulnerabilities in dependencies often necessitates major version updates, accounting for 24% of cases.
Dependency vulnerabilities are not being reported or patched fast enough
The report also sheds light on the delay in reporting and patching dependency vulnerabilities. It reveals that 69% of advisories are published after a patch has been released, with a median delay of 25 days between patch availability and advisory publication.
AI libraries are making vulnerability management more difficult
The rise of artificial intelligence (AI) libraries is adding another layer of complexity to dependency vulnerability management. Inconsistent vulnerability reporting in AI libraries, coupled with phantom dependencies, is a recurring issue. Phantom dependencies, often found in AI and machine learning projects, can introduce vulnerabilities that are hard to detect.
While the prevalence of phantom dependencies varies, the report highlights that over 56% of businesses with significant phantom dependencies reported vulnerabilities in these hidden libraries.
Security pros are being overwhelmed with irrelevant vulnerability alerts
Inaccurate and incomplete data in advisories contribute to false positives and false negatives, complicating the work of security professionals. Furthermore, a lack of code-level vulnerability information in public databases makes it challenging to assess the actual risk posed by vulnerabilities.
Identifying connections between applications and vulnerabilities within their dependencies remains a technical challenge. However, prioritizing vulnerabilities based on reachability analysis data can help streamline remediation efforts and reduce costs.
The benefits of updating the top 20 Python components
Updating dependencies to non-vulnerable versions can have a significant impact on reducing the number of vulnerabilities. For instance, updating the top 20 Python components led to the removal of over 75% of vulnerability findings. By filtering out vulnerabilities that are not reachable or have low exploit potential, security professionals can focus on addressing critical issues effectively.
The report emphasizes the importance of context-based scoping strategies in prioritizing vulnerabilities, ultimately saving organizations valuable time and resources.
As organizations navigate the complexities of dependency vulnerabilities, staying informed and adopting proactive measures are essential in safeguarding software supply chains and mitigating security risks.