Confidence in Agentic Code Fixes is rising – but not without a strong ASPM program

The latest analysis from 451 Research and Daniel Kennedy indicates that security leaders are citing a lack of coordination between AST tools as a major pain point – and the complexity of application security tools is the #1 issue for InfoSec experts today.

The Rise of Agentic AI — and the New Security Imperative

In 2025, software supply chain security (SSCS) is the security leaders’ frontline.

According to an analysis done of the recent Voice of the Enterprise: Information Security, Application Security 2025 survey, SSCS is paramount for ensuring “the integrity and provenance of code artifacts in the development pipeline, and the security of developer tools.” The analysis goes on to cite the top three pain points of security leaders today; including the complexity of AST tools (#1), and lack of coordination between application security testing tools (#3). 

The driving innovative force behind heightened supply chain concerns is breakneck code creation – facilitated by AI.

AI has accelerated software creation beyond human scale and it’s not slowing down. Developers using AI coding assistants generate 3-4× more code and 10× more security findings on average. With 30% of enterprise code already AI-generated and 75% of engineers expected to use AI assistants by 2028, the traditional security stack simply can’t keep up.

That’s why Application Security Posture Management (ASPM) is emerging as the connective tissue for the next wave of agentic code fixes. And security leaders are taking notice.

From Fragmented Tools to Coordinated Intelligence

The research highlights a chronic problem: complexity.

• 28% of respondents cite tool complexity as the top AppSec pain point.
• 25% struggle with lack of coordination across AST tools.
• 15% plan to implement ASPM this year.

ASPM unifies static, dynamic, and open-source analysis tools under one orchestrated layer — correlating results, eliminating duplication, and providing a real-time map of application risk. But in the era of agentic AI, ASPM must evolve beyond correlation. It must activate that intelligence.

Why ASPM Is the Foundation for Agentic Code Fixes

Agentic AI systems – like Apiiro’s AutoFix AI Agent – rely on continuous context to make code fixes. They don’t just scan or flag vulnerabilities; they decide whether to fix, enforce, or accept a risk based on the real runtime environment, policy, and business impact.

That level of decision-making demands a data substrate that can:

• Aggregate and correlate signals from every security tool and code repository.
• Model software architecture and runtime dependencies dynamically.
• Map findings to business risk through governance and policy context.

In short, it requires ASPM.

Without an ASPM layer, agentic AI operates blind – unable to distinguish between a critical, exploitable risk and a low-severity issue already mitigated by compensating controls. The lack of universal adoption of ASPM is why only one-third (33%) of survey respondents said they were “very confident” in “applying AI-generated code fixes  to address identified vulnerabilities.”

Apiiro handles that first point – correlation – by interpreting and collating disconnected signals using Deep Code Analysis. Basic Git diffs are contextless, but DCA connects via API to your source code manager to provide a deep, contextual, and lightweight understanding of software and supply chain architecture. 

Apiiro AutoFix takes it a step further by modeling runtime dependencies dynamically; automatically prioritizing risks, and automatically fixing SAST, SCA, secrets, API, and other security findings. It’s just as lightweight as the DCA that graphs out your architecture – set up via a simple remote Model Context Protocol (MCP) connection.

AutoGovern is glue that binds code to security policy – it automatically enforces policies, standards, and secure coding guardrails. AutoManage wraps it all up neatly, tracking the full lifecycle of every risk and presenting them in the context of SLAs, MTTR, WoE, policy adherence, and development velocity impact.

AI Code Fixes Need ASPM to Be Trusted

According to the same VotE study, 76% of respondents are confident in applying AI-generated code fixes. But a majority still want a human in the loop. That hesitation is rooted in trust and context. Without ASPM, automated fixes risk introducing new vulnerabilities or violating internal policies.

ASPM transforms AI from a helper to a trusted actor; one that can not only suggest but also validate its actions through complete visibility into the software supply chain, runtime, and policy landscape.

Key Takeaway

Agentic AI can fix code; ASPM ensures it fixes the right code, the right way.

Together, they mark the future of secure software development — where security is not a gate, but an autonomous, context-aware force multiplier for innovation.

AI-augmented code is here to stay. Grab a demo with Apiiro to see how you can take advantage of agentic velocity – without sacrificing security.