Latio 2026 AppSec Report Highlights AI Code Risks and Demand for Runtime Context
Summary
Latio’s 2026 application security report finds developer experience leads tool-selection priorities, while 56% want better cloud and runtime context. It examines AI code guardrails, supply chain protection and remediation challenges.
Key points
- Survey respondents ranked developer experience first and low false-positive rates second among application security tool-selection criteria.
- Better cloud and runtime context was requested by 56% of respondents, compared with 35% seeking detection and response and 27% seeking AI pentesting.
- Securing AI-generated code and supply chain malware together accounted for 84% of responses about top application security concerns for 2026.
- The report identifies AI-native static analysis and business logic detection as significant advances, while noting challenges with duplicate findings, scan performance and organizational context.
- AI coding guardrail approaches include repository-specific security rules, application context supplied through MCP, and controls over developer endpoints; the report says best practices remain unsettled.
- Supply chain recommendations extend beyond CVE scanning to package malware detection, reachability analysis and remediation support, with trade-offs around patch backporting and minimal container images.
- Latio recommends evaluating tools by remediation speed and backlog reduction rather than finding counts. The supplied excerpts do not specify the survey sample size or detailed recruitment methodology.
Article Details
- Publisher
- Latio
- Scope
- Application security market assessment, 2026 practitioner survey, and buyer guidance for SMB, mid-market, and enterprise environments.
- Key Statistics
- 56% of survey respondents wanted better cloud and runtime context in their current application security tool, the most requested enhancement.
- Securing AI-generated code and supply chain malware together accounted for 84% of responses concerning top 2026 application security priorities.
- 42% of respondents assigned runtime application security incident handling to the SOC, compared with 31% to product security and 17% to developers.
- Respondents expected core application security offerings to include SCA (52%), SAST (51%), and secrets scanning (49%).
- 46% of respondents selected no bundling when asked what their application security tool should provide.
- Recommendations
- Evaluate application security tools by developer experience, false-positive reduction, and time to fix rather than the number of findings.
- Modernize in-pipeline code reviews with AI-based analysis and business logic vulnerability detection.
- Combine runtime function-level reachability with cloud context to prioritize vulnerabilities and reduce false positives.
- Use pre-commit secret detection and blocking to prevent secrets from reaching upstream repositories.
- Rebuild container images nightly and regularly rebuild and redeploy software to incorporate security patches.
People
Vendors
AikidoSeveral application platform startups like Aikido and Arnica focused on orchestrating andCheckmarxincumbents like Checkmarx and Veracode began speeding up their scanning engines for inCorgeaPost-AI startups, like Corgea and Zeropath, are the leaders in these capabilities, while manyGitGuardianGitGuardian invested heavily in the capabilities, building a platform around them, alongsideGitHubThese changes introduced a new wave of development and observability tools, from GitHubKonvuNewer startups like Aisle, Backline, and Konvu have made meaningful progress generating endPalo Alto NetworksPalo Alto Networks brings a cloud-centric perspective through its broader platform. Each ofSnykto DataDog. At the same time, solutions like WhiteSource (now Mend), Sonatype, and SnykWizassessments of public facing endpoints. To give two examples of AI Pentesting, one is Wiz’sZeropathPost-AI startups, like Corgea and Zeropath, are the leaders in these capabilities, while many
Products
Checkmarx Onelooking to modernize application security at scale, the Checkmarx One platform offers strong coverage acrossCortex CloudPalo Alto Networks Cortex Cloud is a strong fit for security teams looking for integrated scanning or to extract moreEvo by Snykacross their code base. Most recently, Evo by Snyk brings many of the capabilities of dedicated AI security toolsGitHub Advanced SecurityGitHub Advanced Security has quickly become a strong competitor across traditional application security categories,GitHub Copilotcombining security campaigns with GitHub Copilot to make the remediation process as seamless and automated asLegit VibeGuardWith the recent launch of VibeGuard, Legit Security is on the front lines of addressing challenges with AI codeMicrosoft Defender for Cloudintegration with Microsoft Defender for Cloud to analyze and establish runtime risk, GitHub stands out as a strong