45% Say Security Is Harder Now: Here’s How Defense in Depth Helps
Compared to just two years ago, nearly half of security leaders say operations are more difficult. The reasons? An ever-expanding attack surface, a flood of disconnected alerts, and the accelerating pace of threats, many powered by automation and AI.
Based on research from Enterprise Strategy Group (ESG), our partner for our latest whitepaper, AI-Augmented Offensive Security for the Modern Threat Landscape, organizations cite five core challenges: attack surface growth, alert fatigue, tool sprawl, data overload, and the operational burden of maintaining modern security tech.
Security leaders are recognizing that traditional, siloed approaches are insufficient. What’s needed is a resilient, adaptive model: one that integrates offensive testing into every layer of the technology stack. Defense in depth (DiD) delivers that.
What is defense in depth? Defense in depth is a layered cybersecurity strategy that addresses vulnerabilities at every stage of an attack. By combining tools, processes, and resources, it creates an integrated security framework to tackle modern security challenges.
Here’s how that strategy simplifies complexity and strengthens resilience across today’s top five most urgent security challenges.
1. The Expanding Attack Surface
Modern enterprises operate across sprawling ecosystems: public clouds, internal microservices, SaaS platforms, APIs, IoT, and remote endpoints. Each new integration point or exposed asset introduces another potential path to compromise, resulting in visibility gaps and mounting uncertainty.
Solution with Defense in Depth
To manage distributed risk, organizations need continuous, integrated testing across their evolving environments to map and assess the full breadth of a digital ecosystem, from web apps to cloud infrastructure:
- Penetration testing solutions like HackerOne Pentest deliver methodology-driven assessments with real-time visibility into known and unknown asset exposure.
- Bug Bounty and Vulnerability Disclosure Programs (VDPs) provide persistent, researcher-led adversarial testing in production systems.
- Organizations should leverage adversarial methods to continuously identify and mitigate gaps that automated scanners may miss, gaining insights into hidden risks through a global community of researchers.
2. Rapidly Evolving Threat Landscape
At a time when 72% of organizations deploy new builds to production at least once a week, security threats now evolve as fast as software releases. AI-driven malware, LLM prompt injection, and supply chain attacks are just a few examples of adversaries' constant innovation.
With shorter development cycles and new technologies being adopted at speed, security teams must anticipate and test for threats that have no clear signature or precedent.
Solution with Defense in Depth
To stay ahead of modern adversaries, organizations need a layered strategy that continuously probes for emerging risks and adapts faster than attackers:
- Targeted, time-boxed adversarial tests, like HackerOne Challenge, deliver high-signal results by leveraging the creativity and experience of curated researchers. The model succeeds at uncovering critical vulnerabilities fast, ideal for validating security before product launches or compliance milestones.
- AI Red Teaming engagements simulate real-world adversarial behavior against AI systems, uncovering safety, security, and reliability issues that internal QA often misses.
- AI security agents, like HackerOne’s Hai, analyze platform-wide trends to surface the most relevant attack patterns and suggest where to focus testing efforts for maximum impact.
3. Increasing Volume and Complexity of Security Alerts
SOCs are flooded with alerts, most of which lead nowhere. Without context, prioritization, or validation, teams waste time chasing false positives while real risks stay buried. Alert fatigue erodes confidence, slows down triage, and ultimately increases dwell time for actual threats.
Solution with Defense in Depth
To cut through the noise, teams need human-validated signals and automated prioritization:
- Bug Bounty and VDP programs provide verified, high-impact vulnerabilities with clear reproduction steps and business context.
- AI agents like Hai helps prioritize issues based on exploitability and real-world impact, not just CVSS scores.
- Workflow integrations ensure validated findings are routed directly to developers, enabling faster response and resolution.
4. Surge in Security Data Volume
Organizations are collecting more data than ever, including scan results, attack surface inventories, policy violations, but turning that volume into strategy still remains a challenge. The risk is not just overload but stagnation: a flood of metrics without clarity on what’s getting better, worse, or falling behind.
Solution with Defense in Depth
To make smarter decisions, security leaders need visibility into how vulnerabilities evolve and how they compare to peers:
- An AI agent like Hai that is capable of benchmarking program performance across severity types, asset classes, and remediation velocity.
- Metrics like RoM (Return on Mitigation) to quantify the business impact of fixing vulnerabilities before they’re exploited.
- Platform-wide insights surface emerging risks, recurring trends, and program-level blind spots for continuous improvement.
5. Operational Needs of Security Tech Are Hard to Maintain
Tool sprawl and siloed workflows create friction between security and engineering. Many tools require constant tuning and specialized expertise, and still don’t integrate cleanly into modern DevSecOps pipelines.
The result is inefficiency: high overhead, redundant efforts, and inconsistent remediation tracking. In fact, nearly a third of teams say their operations are bogged down by manual processes.
Solution with Defense in Depth
To scale securely, organizations need a platform that automates low-value tasks and integrates seamlessly across the SDLC:
- Developer-friendly AppSec tools analyze pull requests in real time and help catch issues early without slowing down releases. Code review solutions like HackerOne Code blend AI-powered detection with expert validation, delivering actionable findings directly inside tools like GitHub and Azure DevOps.
- Vulnerability elimination workflows manage findings from submission to remediation across all programs.
- Smart agents like Hai automate triage and provide remediation guidance to reduce mean time to resolve (MTTR).
- Native integrations with tools like Jira, GitHub, and Splunk keep security and engineering aligned without added friction.
Secure Your Business with HackerOne’s Defense in Depth
Security leaders are under pressure to reduce risk and prove outcomes, all while modernizing infrastructure and adopting AI. The answer isn’t more tools; it’s an integrated, intelligence-led approach that turns vulnerability discovery into risk elimination.
HackerOne combines the scale of automation and the power of AI with the creativity of human researchers, providing real-time, validated insight across every layer of your technology stack.
Read our latest whitepaper, AI-Augmented Offensive Security for the Modern Threat Landscape, and learn how to turn complexity into control.
