Java Services Face High Security Risks, DevSecOps Must Adapt

The importance of cybersecurity in software development is underscored by recent findings reported in Datadog’s State of DevSecOps. Java services in production are highlighted as especially vulnerable, with an alarming 90% containing at least one vulnerability of critical or high severity—a figure that starkly surpasses the 47% average seen in services using other programming languages. The main contributors to this high vulnerability rate are indirect dependencies. These are the secondary libraries that are incorporated alongside the directly used ones. They account for 63% of the identified security risks. This trend points to a pressing need for better security practices and more stringent management of both direct and indirect dependencies within the Java development ecosystem to mitigate potential cyber threats.

The Third-Party Library Quandary

Third-party libraries are ubiquitous in modern software development due to their efficiency in providing out-of-the-box functionality. However, they also pose serious security risks. For Java services, the reliance on these libraries makes them more susceptible to vulnerabilities, many of which are critical or high in severity. Despite the known risks, these libraries remain integral to Java applications. The indirect nature of many dependencies complicates their tracking and update process, thereby amplifying the security risk. Developers might patch direct dependencies, but often these indirect, or transitive, dependencies are left unchecked, providing a backdoor for attackers.

What’s more alarming is the potential impact of the Known Exploited Vulnerabilities (KEV) catalog by CISA. Java applications are disproportionately targeted, with 55% of these known vulnerabilities affecting Java platforms. This is in stark contrast to the mere 7% affecting other languages, pushing to the forefront the need for Java services to be more diligently scrutinized and secured.

The Need for a Paradigm Shift

DevSecOps must evolve to tackle vulnerabilities more adeptly. Currently, many organizations depend on “ClickOps”—manual protocols for security review and troubleshooting—which are not as swift as automated systems. These practices can cause delays in updating defenses, exposing systems unnecessarily. Transitioning towards automated and continual processes like CI/CD can enhance the speed and efficiency of vulnerability management.

A key step beyond just finding security flaws is accurately gauging how dangerous they are. Tools such as the Exploit Prediction Scoring System (EPSS) prove vital in reassessing the danger level of identified vulnerabilities. Notably, over half of the services initially marked with critical vulnerabilities were downgraded in threat level upon re-evaluation with EPSS. Such precise prioritization helps organizations focus on truly critical issues, optimizing resource allocation for enhanced security measures.

Prioritization and Streamlining Are Key

Recent analysis suggests that when it comes to vulnerability management, factors such as exploitability and context are key, not just severity. Interestingly, a link was found between container size and security—smaller containers generally have fewer vulnerabilities due to fewer components. This highlights the need for a strategic approach to vulnerability management.

Security teams, however, face challenges with scanner tools that can overwhelm them with alerts, including both critical and less impactful vulnerabilities. This situation risks essential threats being missed due to alert fatigue.

Therefore, it’s imperative that DevSecOps practices evolve. Automating security processes, reassessing vulnerability criticality, reducing container sizes, and managing alerts effectively are vital steps for safeguarding Java services in production. Execution of these strategies will enable organizations to strengthen their defense mechanisms in a constantly evolving security ecosystem.

Explore more

ARPA-H Invests $32M in Autonomous Robotic Stroke Treatment

Redefining the Race: The Clock in Stroke Intervention When a blood clot suddenly lodges in a cerebral artery, the human brain begins to lose roughly two million neurons every single minute that the obstruction remains in place. This reality defines the urgency behind a $32 million investment from the Advanced Research Projects Agency for Health (ARPA-H). The funding targets Magnendo,

Can AI Ever Replace Human Intuition in Modern Hiring?

A seasoned hiring manager tosses a candidate’s profile aside while claiming the person simply did not have the right energy, leaving a nearby data analyst completely baffled. To an advanced artificial intelligence, this feedback is a dead end—a vague data point that offers no actionable insight for a machine-learning model. To a veteran recruiter, however, this phrase is a coded

AI Hiring Tools Are Now a Major Security Risk for CIOs

The unassuming PDF file sitting in a digital stack of applications has quietly evolved from a static career summary into a sophisticated piece of executable code capable of hijacking enterprise logic. For decades, recruitment software lived in the relative safety of the back office, primarily serving as a repository for record-keeping and workflow automation. However, the rapid integration of artificial

AI and Remote Work Fuel a Costly Crisis in Hiring Integrity

The polished professional currently answering technical questions on a high-definition video call might actually be an elaborate digital facade powered by a sophisticated network of hidden AI agents. Recruitment processes that once relied on physical cues and verified histories have been subverted by a wave of technological deception that threatens the very core of corporate integrity. As organizations expanded their

Top Eight Free Marketing Analytics Tools for 2026

The persistent pressure to squeeze meaningful insights out of a tightening balance sheet has transformed the role of the modern marketer into a blend of financial strategist and data scientist. In the current economic environment, where the margin for error in customer acquisition has thinned to almost nothing, the ability to interpret data without incurring massive overhead is no longer