apisec compared to Checkmarx, Snyk, Veracode and Black Duck

The short answer

Checkmarx, Snyk, Veracode and Black Duck are application security testing platforms. They find possible flaws in source code, binaries and open source dependencies with SAST and SCA, then use AI agents to triage those findings and generate fixes.

apisec is an Application Exploit Validation platform. It discovers every application from SAST, SCA, API gateways, API platforms and cloud infrastructure, builds a graph of how each one operates, and generates exploits that attempt to compromise the live application. It delivers a SAST report, an SCA report and, most important, actionable exploits that go to the top of the fix queue. It tests with or without source code.

The core difference: the four platforms tell you where flaws might be, and their AI judges which ones matter. apisec tells you which ones an attacker can actually use, with replayable evidence, and confirms each fix by rerunning the attack. apisec is built as the successor to code-only testing, for teams whose problem is no longer finding issues but knowing which ones are real.

The four platforms at a glance

• Checkmarx. Core strength: deep source code analysis across a large portfolio. AI layer: Triage and Remediation Assist agents. Exploitability: AI reasons about reachability from code, and a person reviews anything marked "Proposed Not Exploitable." Fix confirmation: fix pull request, human review, next analysis.
• Snyk. Core strength: developer-first security in the IDE, pull request and coding agent. AI layer: Evo agents aiming for "backlog zero," plus AI pentesting. Exploitability: reasoning-driven AI pentesting you schedule, and deterministic engines for code. Fix confirmation: generated fix, with offensive testing checking it holds.
• Veracode. Core strength: portfolio-wide risk management and compliance reporting. AI layer: Risk Manager and Veracode Fix. Exploitability: prioritization with exploit intelligence and CISA KEV. Fix confirmation: AI patch, next analysis.
• Black Duck. Core strength: open source, license and binary analysis. AI layer: Signal agents and Agentic Fix. Exploitability: AI triage with ContextAI vulnerability intelligence. Fix confirmation: re-scan of the fixed code, then human review.
• apisec. Core strength: proof against the running application, with or without source. AI layer: models generate exploits, and a deterministic harness decides what's real. Exploitability: the attack runs against the live application and succeeds or fails. Fix confirmation: the same exploit reruns and flips from confirmed to cleared.

In their own words: the list is the problem

You don't need to take our word that more findings haven't made anyone safer. All four vendors published the evidence themselves in 2026:

• Veracode: 82% of organizations carry security debt, known flaws left open for more than a year, up from 74%.
• Checkmarx: 75% of organizations knowingly deploy vulnerable code, and 93% reported a recent breach tied to their own applications.
• Snyk: roughly 8 new vulnerabilities are introduced for every one remediated, and new critical and high issues grew 10x in a year.
• Black Duck: the average codebase carries 581 open source vulnerabilities, up 107% in a single year.

Shift left worked. Every commit is analyzed. The result is a list that grows faster than any team can triage it, and AI-generated code is making it grow faster still. The question every security leader now gets is simple: of everything on that list, what can an attacker actually use, and when will it be closed?

How the four platforms manage the backlog today

Each vendor shipped AI agents in 2026 to shrink its own output. That's the tell: the output had become the problem. The approaches differ, but they share three limits.

1. The verdict is a judgment, not proof. Checkmarx's triage agent marks findings "Proposed Not Exploitable" for a person to confirm. Black Duck and Veracode rank findings with AI and vulnerability intelligence. Snyk's own VulnBench research found LLM security reviews report a finding that vanishes on the next run 49.7% of the time. A model reasoning about code can be wrong in either direction.
2. Fixing everything isn't fixing what matters. Snyk and Black Duck now generate fixes at machine speed. A generated fix for a flaw no attacker could reach is still a change someone has to review, test and ship.
3. A re-scan isn't a retest. When a fix passes the next code analysis, it shows the flaw pattern changed, not that the attack no longer works.

Snyk goes furthest at runtime: its Evo Continuous Offensive Security runs AI pentests against running applications for BOLA and business logic flaws. Those deeper assessments run when you schedule them, are reasoning-driven, and skip the bugs Snyk's scanners already found, so the scanner backlog is fixed rather than proven. The full detail for each vendor is in the comparisons below.

Do you still need SAST and SCA?

No. If the question that matters is "can an attacker use this?", then buying more ways to generate findings is a step in the wrong direction.

Detection is no longer scarce. Frontier and open-weight models now find weaknesses that once took a specialist weeks, for pennies per attempt. Finding possible issues has become cheap. Knowing which ones are real has not.

People are the constraint. Every finding costs triage time whether it's real or not. When the bottleneck is people, more findings make the bottleneck worse.

Code is not the application. Exploitability lives where code meets identity, configuration and infrastructure at runtime. A list of thousands of places you might be vulnerable doesn't answer the board's question: how much of our footprint can an attacker use today, and when will it be closed?

apisec is the successor to SAST and SCA

SAST and SCA were built for an era when finding weaknesses was hard and slow. That era is over. apisec is built for the job that's left: it still delivers SAST and SCA reports, but its output is a short list of proven exploits, and every finding you already have becomes a candidate to prove or clear, not a queue to work through.

Spend on proof. Detection without proof just grows the list.

How apisec works

apisec is Application Exploit Validation: see every way in, prove what an attacker can use, confirm the fix.

• apisec Surface builds the application inventory from SAST, SCA, API gateways, API platforms and cloud infrastructure, including shadow and undocumented applications.
• The apisec App Model is a graph representation of how each application operates: routes, identities, authentication, authorization, data flows, dependencies, agents and MCP servers.
• apisec Exploit Testing uses the graph to generate an inventory of application security exploits and runs them against the live application across six layers: business logic, data access, roles and permissions, the application container, infrastructure and security controls. Each is recorded as confirmed, cleared or blocked, with replayable evidence.

What apisec delivers

• A SAST report on first-party code
• An SCA report on open source and third-party dependencies
• Most important: actionable exploits, proven against the running application, with evidence and the data each one exposed, at the top of the fix queue

With or without source code

Much of what runs in a modern application is code you never receive: cloud frameworks, managed services, gateways, vendor SDKs. SAST and SCA can only analyze what you hand them. apisec tests the running application, so it covers that code the way an attacker meets it. When source is available, apisec uses it to enrich the App Model and produce the SAST and SCA reports. When it isn't, testing still runs.

Models help generate exploits and explanations. A deterministic harness decides what's real, so the same application gives the same answer every run.

Detailed comparisons

• apisec compared to Veracode: Veracode's own data shows 82% of organizations carry security debt. Prioritization and AI patches make the queue manageable; they don't prove what's in it.
• apisec compared to Checkmarx: Checkmarx's triage agent proposes which findings aren't exploitable, and a person still has to decide. apisec runs the attack instead.
• apisec compared to Snyk: Snyk aims to fix the whole backlog and adds scheduled AI pentesting. apisec proves what matters continuously, with a deterministic harness.
• apisec compared to Black Duck: Black Duck's Agentic Fix validates fixes by re-scanning code. apisec confirms them by rerunning the exploit.

Frequently asked questions

How does apisec compare with Checkmarx, Snyk, Veracode and Black Duck?

Checkmarx, Snyk, Veracode and Black Duck find possible flaws in code and dependencies, then use AI agents to triage and fix them. apisec proves which weaknesses an attacker can actually exploit by running attacks against the live application, records each as confirmed, cleared or blocked with replayable evidence, and reruns the attack to confirm every fix.

Is apisec an alternative to SAST and SCA tools?

Yes. apisec is built as the successor to code-only testing. It still delivers a SAST report and an SCA report, but its main output is actionable exploits proven against the running application, which go straight to the top of the fix queue. Teams use it to replace a growing findings backlog with a short list of confirmed exploits.

Why do SAST and SCA tools produce so many false positives?

SAST and SCA judge exploitability from code and package versions without the running application in front of them. They can't see the middleware, gateway or configuration that blocks a path, or whether a vulnerable library function is ever reached. So they report possibilities, and someone has to investigate each one. apisec tests the attack instead.

These platforms already use AI to triage findings. Why isn't that enough?

AI triage still reasons about code, so its verdict is a judgment a person often has to confirm, and model-based reviews can change their answer between runs. apisec runs the attack against the live application with a deterministic harness, so the same application gives the same answer every run, and every result comes with replayable evidence.

Does apisec need access to source code?

No. apisec tests the running application with or without source code. That matters for third-party code you never see, such as cloud frameworks, managed services and vendor components, and for how open source libraries behave inside your application. SAST needs the code and SCA matches declared packages to known CVEs; apisec tests what actually runs.

See what an attacker can use in your application

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