ArmorCode Survey Finds Over Half of Security Leaders Struggle with Programs
- Just over half of the 200 senior security and technology leaders polled in a survey by ArmorCode say their organizations will struggle to simplify their software security programs...
- When a scanner detects a vulnerability in enterprise code, manual intervention is required to determine if the flaw matters, identify ownership, and push a fix through engineering teams...
- Simultaneously, the volume of code requiring review has grown as developers adopt artificial intelligence coding assistants.
Just over half of the 200 senior security and technology leaders polled in a survey by ArmorCode say their organizations will struggle to simplify their software security programs if they continue working their current way, according to findings reported by Help Net Security. Most respondents hold senior roles at enterprises with 10,000 or more employees, facing operational bottlenecks immediately after automated scanners flag a potential flaw.
Manual Intervention Delays Critical Vulnerability Resolution
When a scanner detects a vulnerability in enterprise code, manual intervention is required to determine if the flaw matters, identify ownership, and push a fix through engineering teams running on separate release schedules. Each handoff introduces friction and leaves known software flaws exposed for extended periods. Verizon’s 2026 Data Breach Investigations Report sets the median time to fully resolve a critical vulnerability at 43 days.
Simultaneously, the volume of code requiring review has grown as developers adopt artificial intelligence coding assistants. Forty percent of survey respondents identified the sheer volume of AI-generated code waiting for human review as their most significant software security challenge. While AI code is not inherently insecure, automated generation outpaces the capacity of human security reviewers.
Tiered Automation Strategies for Vulnerability Discovery
To manage incoming volume, 44 percent of participants named a tiered strategy for AI-assisted vulnerability discovery as their primary transformation need. Rob Chapman, a principal solutions engineer at ArmorCode, outlined a three-tiered operational model to Help Net Security.
Automation should handle deterministic work: findings, remediations, and mitigations that are repeatable, low risk, and well understood. Most organizations already have some degree of this in place. These findings fit well into workflows built on mature processes such as normalization, enrichment, ownership routing, ticket management, SLA management, and rescan verification.
Rob Chapman, ArmorCode
The middle layer utilizes AI agents to handle tasks requiring multi-step reasoning with limited supervision. Chapman noted that these agents can assess signals for reachability and exploitability, identify correlated findings, and map potential attack paths under strict guardrails. Meanwhile, human staff retain final ownership of risk acceptance and exceptions.
Consolidated Tools Reduce Low-Context Security Alerts
Beyond review volume, respondents highlighted a pervasive flood of low-context alerts. These notifications flag weaknesses without indicating whether a system is reachable, whether an exploit is realistic, or which business service depends on the affected asset.
To reduce tool sprawl, Chapman advised consolidating applications where functions overlap and signal quality is redundant. Organizations are encouraged to keep specialized tools that offer unique coverage and connect them through a common data layer.
Executive Leadership Tracks Remediation Time and Operational Hot Spots
When reporting risk to executive leadership, security teams must track specific operational metrics. Chapman stated that the primary metric remains the time required to remediate meaningful exploitable and exposed systems.
Leaders also require visibility into regional business units and product teams to locate support needs and emerging operational hot spots across the enterprise risk surface.