CVE-2025-1752: LlamaIndex's Web Crawler Takes an Infinite Dive, and Your Python Process Pays the Price!

Robert Morgan

Robert Morgan

— 7 min read

Heard the one about the web crawler that got stuck in a loop? It's not just a bad joke; it's a reality for users of LlamaIndex versions prior to 0.12.21 due to CVE-2025-1752. This vulnerability in the KnowledgeBaseWebReader could send your Python process into a recursive nosedive, leading to a Denial of Service (DoS). Let's unpack this digital rabbit hole!

TL;DR / Executive Summary

Vulnerability: CVE-2025-1752 - Denial of Service (DoS) in LlamaIndex.
Affected Component: KnowledgeBaseWebReader class within the run-llama/llama_index project.
Affected Versions: llama-index versions >= 0.12.15 and < 0.12.21. Specifically, llama-index-readers-web versions before 0.3.6.
Impact: An attacker can craft a malicious web page that, when processed by the KnowledgeBaseWebReader, causes excessive recursion. This exhausts Python's recursion limit, leading to resource consumption and ultimately crashing the Python process.
Severity: While no official CVSS score is available at the time of writing, the direct impact is a DoS, which can range from Medium to High severity depending on the application's criticality.
Basic Mitigation: Upgrade llama-index to version 0.12.21 or later, or ensure llama-index-readers-web is at version 0.3.6 or later.

Introduction: The Insatiable Thirst for Knowledge (and Web Pages)

In the age of Large Language Models (LLMs), data is king. Projects like LlamaIndex are invaluable tools, acting as a central interface to connect your custom data sources to LLMs. One common way to feed these hungry models is by scraping websites, and LlamaIndex provides the KnowledgeBaseWebReader for just this purpose. It's designed to intelligently crawl through knowledge bases, like FAQs or documentation sites, extracting juicy information.

Imagine you're building a sophisticated AI assistant that needs to understand your company's entire online documentation. You point KnowledgeBaseWebReader at your support portal, and it diligently starts mapping out the articles. But what if this diligent crawler encounters a cleverly booby-trapped site? That's where CVE-2025-1752 comes into play. This vulnerability matters because it can bring any LlamaIndex-powered application relying on this web reader to a screeching halt, simply by feeding it a malicious URL. For anyone building RAG (Retrieval Augmented Generation) pipelines or knowledge ingestion systems, this is a critical bug to understand and patch.

Technical Deep Dive: Down the Recursive Rabbit Hole

Let's get our hands dirty and see what went wrong.

The Vulnerability: Unchecked Recursion

The core of CVE-2025-1752 lies within the get_article_urls method of the KnowledgeBaseWebReader class. This function is responsible for recursively crawling web pages to find links to articles. It takes a max_depth parameter, which should limit how many levels deep the crawler ventures. However, prior to the fix, this parameter wasn't being correctly honored.

Here's a simplified look at the problematic logic (conceptually similar to the vulnerable code):

# Conceptual representation of the vulnerable logic
class KnowledgeBaseWebReader:
    # ... other methods ...

    def get_article_urls(self, browser: Any, root_url: str, current_url: str, max_depth: int = 100) -> List[str]:
        # ... page loading and initial link scraping ...
        # page = browser.new_page()
        # page.goto(current_url)
        # links = page.query_selector_all("a.article-link") # Example selector
        
        article_urls = []
        # ...
        
        # THE VULNERABLE PART:
        # 'max_depth' is passed along, but no current 'depth' is tracked or checked against it effectively.
        for link_element in links:
            # href = link_element.get_attribute('href')
            # next_url = root_url + href 
            # article_urls.extend(
            #    self.get_article_urls(browser, root_url, next_url, max_depth) # Oops! No depth increment or check
            # )
        
        # ...
        return article_urls

Root Cause Analysis: The Missing Depth Gauge

Think of recursion like exploring a cave system. max_depth is supposed to be your safety rope, telling you how many turns or levels deep you can go before you must turn back. The problem was that while the max_depth value was passed along in each recursive call, the function wasn't keeping track of its current depth. It was like having a 100-meter rope but never checking how much of it you've already used.

Each time get_article_urls found new links, it would call itself to process those links. If a website had a very deep structure, or worse, a circular link structure (e.g., Page A links to Page B, and Page B links back to Page A), the function would call itself over and over again. Python, like most programming languages, has a recursion limit (typically around 1000-3000 calls) to prevent infinite loops from consuming all available stack memory. Without a proper depth check against max_depth, a malicious site could easily force the crawler to exceed this limit.

Attack Vectors

An attacker could exploit this by:

  1. Crafting a Malicious Website: The attacker sets up a website with either an extremely deep link structure (e.g., page1 links to page2, page2 to page3, ... page1001) or pages that link back to each other in a loop.
  2. Luring the Crawler: The attacker tricks an application using the vulnerable LlamaIndex version to crawl this malicious website. This could be through direct input if the application allows users to specify URLs, or by compromising a legitimate site that the application is expected to crawl.

Business Impact

The primary impact is a Denial of Service (DoS):

  • Application Crash: The Python process running the LlamaIndex application will crash with a RecursionError.
  • Resource Exhaustion: Before crashing, the process might consume significant CPU and memory.
  • Service Unavailability: Any service relying on this LlamaIndex instance for data ingestion or processing becomes unavailable. For a customer-facing AI chatbot or an internal knowledge search, this means downtime and disruption.

Proof of Concept (Conceptual)

While setting up a full Playwright environment and a live malicious server is beyond a blog post snippet, we can illustrate the core issue.

Imagine an attacker's server malicious-site.com has two pages:

  • malicious-site.com/pageA contains a link to malicious-site.com/pageB
  • malicious-site.com/pageB contains a link back to malicious-site.com/pageA

If a LlamaIndex application using the vulnerable KnowledgeBaseWebReader is pointed to malicious-site.com/pageA:

# Simplified conceptual usage (vulnerable version)
# from llama_index.readers.web import KnowledgeBaseWebReader # Fictional import for older structure
# reader = KnowledgeBaseWebReader() 
# Assume 'browser' is a Playwright browser instance

# This call would eventually lead to a RecursionError
# reader.get_article_urls(browser, "http://malicious-site.com", "http://malicious-site.com/pageA", max_depth=10)

The get_article_urls function would:

  1. Load pageA, find link to pageB.
  2. Call get_article_urls for pageB (depth effectively 1, but not tracked).
  3. Load pageB, find link to pageA.
  4. Call get_article_urls for pageA (depth effectively 2, but not tracked).
  5. ...and so on.

Even with max_depth=10, the calls would continue pageA -> pageB -> pageA -> pageB ... far exceeding Python's actual recursion limit, because the max_depth parameter wasn't being used to stop the descent.

Mitigation and Remediation: Patching the Hole

The good news is that this vulnerability has been addressed!

Immediate Fixes:

  • Upgrade LlamaIndex: The primary solution is to upgrade your llama-index package to version 0.12.21 or later.
    pip install "llama-index>=0.12.21"
  • Upgrade Specific Reader (if managed separately): If you manage llama-index-readers-web directly, ensure it's version 0.3.6 or later.
    pip install "llama-index-readers-web>=0.3.6"

Patch Analysis: How the Fix Works

The fix, introduced in commit 3c65db2947271de3bd1927dc66a044da385de4da, is elegant and straightforward. It involves two key changes to the get_article_urls function in llama-index-integrations/readers/llama-index-readers-web/llama_index/readers/web/knowledge_base/base.py:

  1. Introduction of a depth parameter: The function signature was changed to include a depth parameter, initialized to 0 for the first call.

    -        self, browser: Any, root_url: str, current_url: str, max_depth: int = 100
+        self,
+        browser: Any,
+        root_url: str,
+        current_url: str,
+        max_depth: int = 100,
+        depth: int = 0,

  2. Depth Check and Increment:

    • At the beginning of the function, a check is added:
      +        if depth >= max_depth:
+            print(f"Reached max depth ({max_depth}): {current_url}") # Good for debugging!
+            return []
      This is our crucial safety net. If the current depth meets or exceeds max_depth, the function stops recursing and returns an empty list.
    • In the recursive call, the depth is incremented:
      -                self.get_article_urls(browser, root_url, url, max_depth)
+                self.get_article_urls(browser, root_url, url, max_depth, depth + 1)
      Now, with each dive deeper into the website's structure, the depth counter increases, ensuring the max_depth limit is eventually hit if the site is too deep or has loops.

This is a classic example of correctly managing state in recursive functions to prevent unbounded execution.

Long-Term Solutions & Best Practices:

  • Input Validation: Always be cautious about URLs or any input that controls resource-intensive operations like web crawling. If possible, validate domain TLDs or limit crawling to trusted sources.
  • Resource Limiting: For tasks like web scraping, consider running them in isolated environments with resource limits (CPU, memory) at the OS or container level as a secondary defense.
  • Defensive Coding: When writing recursive functions, always ask: "What's my base case? What's my termination condition? How do I prevent infinite recursion?"

Verification Steps:

After upgrading, you can verify the installed version:

pip show llama-index
pip show llama-index-readers-web

Ensure the versions meet or exceed the patched versions.

Timeline of CVE-2025-1752

  • Discovery Date: While not explicitly stated, the fix was committed by a contributor (masci), suggesting a community report or internal discovery.
  • Vendor Notification: Implicitly handled through the GitHub pull request and review process for the run-llama/llama_index project.
  • Patch Commit: 3c65db2947271de3bd1927dc66a044da385de4da (merged into the main branch around May 2024, based on typical development cycles leading to a May 2025 CVE ID placeholder).
  • Patched Version Release (llama-index-readers-web v0.3.6): Shortly after the commit was merged and tested.
  • Public Disclosure (CVE Assignment): The CVE ID CVE-2025-1752 was published with details on 2025-05-10 15:30:28+00:00. (Note: The "2025" in the CVE ID suggests a placeholder or future assignment date; typically, CVEs are numbered for the year of discovery or public disclosure. We're using the provided data.)

"Behind the Scenes" Insight: This fix (PR #17949 by masci) highlights the power of open-source communities. A contributor identified a potential issue, proposed a clear fix, and helped make the LlamaIndex ecosystem more robust. This collaborative approach is vital for security.

Lessons Learned: The Never-Ending Story of Recursion

This CVE serves as a great reminder of some fundamental cybersecurity principles:

  1. Recursion is Powerful, But Handle With Care: Recursive functions are elegant for certain problems (like traversing tree-like structures, e.g., websites), but they must have well-defined, robust termination conditions. Forgetting to pass or check a depth counter is a common pitfall.
  2. Trust, But Verify (External Inputs): When your code interacts with external data or systems (like crawling arbitrary websites), assume the external system might not play nice. KnowledgeBaseWebReader is designed to explore, but that exploration needs guardrails.
  3. The Importance of max_depth (and using it!): Many libraries offer parameters like max_depth or timeout. It's not enough for them to exist; they need to be correctly implemented and tested.

Prevention Practices:

  • Thorough code reviews, especially for recursive functions and input handling.
  • Static analysis tools (SAST) can sometimes flag potential unbounded recursion.
  • Fuzz testing with malformed inputs or structures can uncover such issues.

Detection Techniques:

  • Monitor application logs for RecursionError exceptions.
  • Observe system resources: a process suddenly consuming 100% CPU and growing memory usage before crashing can be indicative of such a loop.

One Key Takeaway:
Even in sophisticated AI/LLM frameworks, foundational programming errors can lead to significant vulnerabilities. Secure coding isn't just about cryptography; it's also about robust error handling, input validation, and managing resource consumption, especially with recursive patterns.

References and Further Reading

This dive into CVE-2025-1752 shows that even a seemingly innocuous feature like web crawling needs careful implementation to avoid becoming an Achilles' heel. So, patch up, stay vigilant, and perhaps double-check your own recursive functions. What other "simple" features in complex systems do you think might harbor hidden recursive risks?

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