Listen to this Post
Introduction:
For a decade, Spotify has operated one of the most recognized bug bounty programs in the industry, partnering with HackerOne to crowdsource security research at scale. On August 19, Spotify Security Engineer Mikhail Chechik will join Chris Foley for a fireside chat revealing the inside story of how the music streaming giant scaled its program from a small email-based operation to a mature security strategy that has awarded $750,000 in bounties. As threats evolve with the rise of generative AI, Spotify’s approach to AI red teaming offers a blueprint for organizations looking to secure the next generation of intelligent systems.
Learning Objectives:
- Understand the evolution of Spotify’s bug bounty program from 2015 to today, including key decisions that shaped its growth
- Learn how organizations can scale vulnerability disclosure programs while maintaining quality and researcher engagement
- Explore the emerging field of AI red teaming and how Spotify is preparing for AI-specific threats like prompt injection and model extraction
You Should Know:
- From Swag to $750,000: The Evolution of Spotify’s Bug Bounty Program
Spotify’s Security team launched its bug bounty program in 2015, when the team was small and vulnerability reports were managed manually through email. At the time, reporters were rewarded with swag or credit on Spotify’s wall of fame. The program moved to HackerOne in May 2017 to leverage the platform’s managed services, triage capabilities, and payment infrastructure.
Today, the program has matured significantly. Over its 10-year run, Spotify has received thousands of reports, awarded $750,000 in bounties, and built a reputation as a model for hacker-powered security. The program uses the Common Vulnerability Scoring System (CVSS) to determine severity, with HackerOne’s triage team reviewing reports for scope, validity, and severity before forwarding them to Spotify’s security team.
Step-by-Step Guide: How to Submit a Vulnerability to Spotify’s Bug Bounty Program
For security researchers looking to participate, the process follows a structured workflow:
- Identify a vulnerability in scope: Spotify accepts reports on its most visible websites (spotify.com, community.spotify.com), mobile applications, desktop applications, and other software. The desktop application is explicitly listed as in-scope on the program page.
-
Submit a report via HackerOne at https://hackerone.com/spotify.
-
HackerOne triage team reviews the report for scope, validity, and severity using CVSS.
-
Spotify Security team investigates valid reports and works with the development team on a resolution.
-
Fix deployed and bounty awarded commensurate with severity through the HackerOne platform.
Linux Command Example: Basic Reconnaissance for Bug Bounty Hunting
Security researchers often begin with reconnaissance. Here’s a basic approach using common Linux tools:
Subdomain enumeration using Amass amass enum -d spotify.com -o spotify_subdomains.txt DNS enumeration with dnsrecon dnsrecon -d spotify.com -t axfr Port scanning with Nmap nmap -sV -p- -T4 spotify.com Web technology detection whatweb https://spotify.com Directory busting with ffuf ffuf -u https://spotify.com/FUZZ -w /usr/share/wordlists/dirb/common.txt
Windows Command Example: PowerShell for Security Research
For Windows-based researchers, PowerShell can be equally powerful:
DNS resolution test Resolve-DnsName spotify.com Test network connectivity Test-1etConnection spotify.com -Port 443 HTTP request testing Invoke-WebRequest -Uri https://spotify.com -Method GET Certificate information Get-PfxCertificate -FilePath "https://spotify.com"
- AI Red Teaming: Securing the Next Generation of Intelligent Systems
As Spotify integrates AI into its platform—from personalized playlists to generative experiences—the security landscape has shifted dramatically. The company is now hiring AI Security Engineers to address vulnerabilities specific to AI/ML systems, including data poisoning, adversarial examples, and model extraction.
AI red teaming has emerged as a critical practice for identifying vulnerabilities before they can be exploited. Unlike traditional penetration testing, AI red teaming focuses on threats like prompt injection, jailbreaking, and data leakage. The MITRE ATLAS framework provides a taxonomy for these threats, including AML.T0051 (Prompt Injection).
Step-by-Step Guide: AI Red Teaming Fundamentals
Organizations looking to implement AI red teaming should follow this structured approach:
- Define the AI system scope: Identify which AI/ML models, data pipelines, and inference endpoints are in scope.
-
Conduct threat modeling: Map potential attack vectors specific to AI systems, including adversarial inputs, model inversion, and membership inference.
-
Develop attack scenarios: Create test cases for common AI vulnerabilities:
– Prompt injection: Crafting inputs that override system instructions
– Data poisoning: Manipulating training data to corrupt model behavior
– Model extraction: Reverse-engineering model parameters through API queries
- Execute automated red teaming: Use specialized tools to test AI systems at scale.
-
Risk assessment and remediation: Score vulnerabilities based on impact and likelihood, then implement mitigations.
AI Security Tools and Commands
Security professionals can use these open-source tools for AI security testing:
Garak - LLM vulnerability scanner pip install garak garak --model_type huggingface --model_name gpt2 PyRIT - Microsoft's Python Risk Identification Tool git clone https://github.com/Azure/PyRIT cd PyRIT python -m pip install -e . Counterfit - AI security testing framework git clone https://github.com/Azure/counterfit cd counterfit pip install -r requirements.txt python counterfit.py
- The Golden Paths Strategy: Building Security into Engineering Culture
Spotify’s bug bounty program informs the company’s “Golden Paths” engineering strategy, which sets out the best way to build products. This consists of a set of APIs, application frameworks, and runtime environments that allow engineers to develop and deploy code securely and at scale.
The approach reflects a shift-left philosophy: security isn’t an afterthought but an integrated part of the development lifecycle. By embedding security into the engineering culture, Spotify reduces the attack surface before code reaches production.
Step-by-Step Guide: Implementing a Golden Paths Security Strategy
- Define secure defaults: Establish approved APIs, frameworks, and runtime environments that include security controls by default.
-
Automate security checks: Integrate SAST, DAST, and dependency scanning into CI/CD pipelines.
GitHub Actions example for dependency scanning - name: Dependency Scan uses: actions/dependency-review-action@v3
- Implement security training: Provide developers with security awareness training tailored to their role.
-
Establish a vulnerability disclosure policy: Formalize how external researchers can report issues.
-
Measure and iterate: Track metrics like mean time to fix (MTTF) and bounty payout trends to improve the program.
Windows PowerShell for Security Automation
Check for exposed secrets in code
Select-String -Path .\ -Pattern "password|secret|key|token" -CaseSensitive
Verify SSL/TLS configuration
Invoke-WebRequest -Uri https://spotify.com
Check open ports on local machine
Get-1etTCPConnection | Where-Object {$_.State -eq "Listen"}
What Undercode Say:
- Key Takeaway 1: Spotify’s 10-year bug bounty journey demonstrates that crowdsourced security isn’t just about finding bugs—it’s about building a culture of security that scales with the organization. The program’s evolution from swag to $750,000 in bounties reflects a deepening commitment to security as a business imperative.
-
Key Takeaway 2: AI red teaming represents the next frontier in offensive security. As organizations integrate LLMs and generative AI into their products, traditional pentesting approaches are insufficient. The MITRE ATLAS framework and specialized tools like Garak and PyRIT are essential for identifying AI-specific vulnerabilities before attackers exploit them.
Analysis: The Spotify case study offers several critical lessons for security leaders. First, bug bounty programs require continuous investment and refinement—Spotify didn’t achieve its current maturity overnight. Second, the integration of bug bounty insights into engineering practices (Golden Paths) creates a virtuous cycle where security improves across the organization. Third, the emergence of AI red teaming signals a paradigm shift: security teams must now defend against attacks that target the logic and training data of AI systems, not just traditional infrastructure. Organizations that fail to adapt risk being left behind as adversaries increasingly target AI-powered features.
Prediction:
- +1 The bug bounty industry will continue to grow as more organizations recognize the value of crowdsourced security, with global spending on hacker-powered security expected to exceed $10 billion by 2030.
- +1 AI red teaming will become a standard practice for organizations deploying LLMs, with regulatory frameworks like the EU AI Act mandating adversarial testing for high-risk AI systems.
- +1 The integration of AI into bug bounty platforms will accelerate, with automated vulnerability triage and AI-assisted report analysis reducing response times significantly.
- -1 The skills gap in AI security will widen as demand for AI Security Engineers outpaces supply, creating a talent shortage that leaves many organizations vulnerable.
- -1 Adversarial AI techniques will become more sophisticated, with attackers using AI to automate vulnerability discovery and exploit generation at scale.
- +1 Spotify’s model of combining bug bounties with internal security engineering will be emulated by other tech giants, creating a new standard for security program maturity.
- -1 The dismissal of local or post-exploitation attack vectors by some bug bounty programs may create blind spots that sophisticated attackers can exploit.
- +1 The MITRE ATLAS framework will evolve to become the industry standard for AI threat intelligence, similar to MITRE ATT&CK for traditional cyber threats.
- +1 Community-driven security will increasingly be seen as a competitive advantage, with companies like Spotify using their bug bounty programs as both security tools and marketing assets.
- -1 The complexity of securing AI systems will lead to an increase in high-profile AI-related data breaches, prompting regulatory intervention and forcing organizations to accelerate their AI security investments.
▶️ Related Video (68% Match):
🎯Let’s Practice For Free:
🎓 Live Courses & Certifications:
Join Undercode Academy for Verified Certifications
🚀 Request a Custom Project:
Secure, high-velocity infrastructure and disruptive technological engineering. Contact our engineering team for high-tier development and proprietary systems:
[email protected]
💎 Smart Architecture | 🛡️ Secure by Design | ⭐ Trusted by Thousands
IT/Security Reporter URL:
Reported By: Bradcall The – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
