CVE-2022-24795: Harden yajl-ruby Against 32-bit Integer Overflow

A deep, quietly dangerous integer‑overflow in the C layer of the popular Ruby JSON binding yajl‑ruby can turn very large JSON inputs into heap corruption and sustained process outages — operators should treat CVE‑2022‑24795 as a practical availability threat on 32‑bit builds and patch immediately, or apply strict input‑size controls and containment until you can. (github.com)

Background / Overview​

yajl‑ruby provides a thin C binding to YAJL (Yet Another JSON Library) so Ruby applications get fast streaming JSON parsing. The vulnerability tracked as CVE‑2022‑24795 stems from an integer overflow in realloc/resize logic inside the C extension: when a parsing routine attempts to grow an internal buffer to accommodate roughly 0x80000000 bytes (about 2 GB), a 32‑bit length ("need") can wrap to zero. The code then reallocates a tiny buffer but later writes using the original (much larger) expected size — producing heap memory corruption and, in real deployments, process crashes and denial of service. (github.com)
The important operational nuance is platform bitwidth: on true 64‑bit builds where size_t is 64 bits this integer wrap is practically unreachable, but on 32‑bit Ruby builds or systems where the extension is compiled for 32‑bit targets, it is exploitable by feeding very large JSON inputs. Major vulnerability trackers and vendors therefore treat the primary impact as availability (crash/DoS) rather than immediate remote code execution, though any heap corruption warrants careful handling. (github.com)

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What the bug is — technical summary​

Where it lives​

• Vulnerable file: ext/yajl/yajl_buf.c (the buffer reallocation routine).
• Vulnerable operation: growth logic that computes how much additional space is needed and repeatedly left‑shifts a need value until it fits; the loop and arithmetic can overflow on 32‑bit widths. (github.com)

Failure mode​

• When need approaches 0x80000000, a signed/unsigned wrap can reduce the computed allocation to a small number.
• realloc returns a small chunk, but subsequent writes assume the larger, pre‑wrap size.
• Result: heap buffer overflow → heap metadata corruption → crash (DoS) or, in the worst case, more dangerous memory corruption chains.

Why this matters in practice​

• Many Internet‑facing applications parse incoming JSON: file uploads, API endpoints, webhooks, inter‑service messages.
• Attacker can deliver a crafted large JSON stream (via a single POST or chunked transfer) to trigger the overflow.
• The most realistic impact is sustained availability loss (process crashes, worker death, service outages) when an attacker repeatedly submits crafted payloads. (github.com)

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Affected versions, exposure model, and patch status​

Affected versions​

• The GitHub security advisory reports affected versions: <= 1.4.2 and patched in 1.4.3. The advisory also notes that a prior patch (1.4.2) addressed the heap corruption but could still allow a DoS infinite loop; therefore the safe target is yajl‑ruby 1.4.3 or later. (github.com)
• Upstream trackers and the NVD list the same root cause (integer overflow at yajl_buf.c#L64) and emphasize that 2.x branch uses size_t which mitigates the condition on 64‑bit builds, but does not fully eliminate risk on 32‑bit builds.

Exposure model​

• Remote, unauthenticated attackers can trigger the condition whenever your application accepts untrusted JSON input and passes it to the vulnerable parser.
• Practical exploitability requires the ability to send multi‑GB payloads or otherwise influence parsing of extremely large JSON structures; not every deployment exposes that vector. However, cloud APIs, file‑upload endpoints, and internal ingestion pipelines sometimes do accept very large inputs and are therefore relevant targets.

Patch and vendor action​

• The maintainer published a GitHub advisory and patched releases; distributions (Debian, Fedora, etc.) backported fixes into packaging trees and downstream vendors issued updates. Operators should prefer vendor packages where available or upgrade the gem to 1.4.3. (github.com)

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Exploitability, risk profile, and realistic outcomes​

Likelihood vs. impact​

• Likelihood: Moderate for internet‑facing services that accept large JSON, low for typical 64‑bit deployments that limit payload sizes.
• Impact: High for services that depend on vulnerable workers — a single crafted request can crash a worker process; repeated requests can exhaust available workers and produce a service outage.

What an attacker can achieve​

• Denial of service (sustained or persistent) by repeatedly sending crafted payloads until processes fail to recover or resource exhaustion occurs.
• Information disclosure and RCE are considered unlikely in most contexts, but heap corruption can be a stepping stone in complex exploitation chains. Treat any heap corruption as serious. (github.com)

Attack complexity and prerequisites​

• The raw technical trigger is straightforward (very large JSON), but real‑world exploitation may need twork and upload limits (application servers commonly cap body sizes).
• Intermediate proxies and gateways that buffer or limit payloads.
• Resource containment such as per‑process memory limits or sandboxing that reduce the likelihood of catastrophic host‑wide failures.

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Detection and hunting​

• Inventory your Ruby apps and gems. Search for yajl‑ruby in lockfiles (Gemfile.lock) and deployed images. Confirm installed versions. If you vendor gems into apps, inspect the bundled gem tree.
• Identify where your apps accept JSON payloads (endpoints, file uploads, worker queues). Prioritize exposure where payload sizes are large or unbounded.
• Add instrumentation: detect anomalous request body sizes, repeated parse errors, or sudden worker crashes associated with JSON parsing.
• Run vulnerability scanning across images and CI/CD to find yajl‑ruby versions <= 1.4.2 in builds and artifacts. Note that static/bundled binaries or vendorized code may carry vulnerable versions even if host packages are patched.

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Ind long‑term remediation​

Immediate (if you cannot upgrade right away)​

• Enforce strict maximum request body sizes at the edge (web server, reverse proxy, CDN): set conservative caps (for example, 10–100 MB) and reject larger requests early.
• Apply per‑process memory limits (cgroups, uliontrol) and run parsers in isolated, short‑lived helper processes so a crash does not take down the entire service.
• Rate‑limit and WAF rules: block clients that repeatedly attempt to send oversized JSONs; set thresholds for request counts and body size. (github.com)

Correct fix​

• Upgrade yajl‑ruby to 1.4.3 or later in your Gemfile and rebuild/deploy. The maintainer’s advisory marks 1.4.3 as the safe release. (github.com)
• If you consume vendor packages, install the vendor security updates or patched OS packages as provided by youristros released errata/backports.
• Rebuild and redeploy any statically bundled artifacts or vendorized gems that were compiled against older sources. Static linking / vendorization means host package updates are not sufficient — the vulnerable code can remain inside the binary.

Verade, run functional tests that parse borderline inputs and ensure memory usage remains bounded.​

• Re‑scan container images and application artifacts to verify that no instance of yajl‑ruby <= 1.4.2 remains in the deployment. Automated SBOM and SCA scans help.

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Developer guidance — hardening parsing code​

• Treat untrusted numeric values and lengths as potentially adversarial. Always validate size and length fields before allocating or copying data.
• Implement defensive checks: reject inputs that would require allocations beyond a configured safe limit (for example, cap arrays and strings during streaming parse).
• Prefer streaming parsers that can process data incrementally with early‑abort on large or malicious payload shapes.
• Consider parsing untrusted payloads inside a dedicated helper process with very small memory/CPU budgets; let a supervisor restart it on failure to contain impact. This reduces blast radius and is a pragmatic isolation pattern.

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Supply‑chain and operational considerations​

• Static/build‑time risk: Go, C, and Ruby artifacts ctive code. Packaging or vendorizing C extensions into application bundles means you must rebuild to eliminate vulnerable code. The general rule: if the vulnerable code was compiled into a binary, you must rebuild that binary with the patched sources to be safe.
• Automated detection: include checks for yajl‑ruby versions in CI, container image scanning, and SBOM generation. Lockfiles (Gemfile.lock) and vendor manifests must be validated during CI gating.
• Patching cadence: prefer vendor/stable distribution patches when available because they integrate with OS packaging and testing; for bespoke builds, schedule rebuilds with the fixed gem and redeploy images.

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Practical checklist for system administrators (actionable steps)​

• Inventory:
• Find all applications that depend on yajl‑ruby (Gemfile, Gemfile.lock, vendor directories).
• Prioritize:
• Rank apps by exposure: public APIs and upload endpoints first.
• Patch:
• Upgrade to yajl‑ruby 1.4.3 and redeploy. If using OS packages, apply ve
• Contain (if you cannot patch immediately):
• Set body size limits, run parsers in isolated helpers, enable memory caps, and add WAF rules.
• Verify:
• Rebuild static/vendorized binaries, run tests that simulate large inputs, and scan images for vulnerable artifacts.
• Monitor:
• Watch for parse‑related crashes, elevated OOM or worker restarts, and unusual client behavior attempting oversized uploads.

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Critical analysis — strengths, remaining risks, and why this needs attention​

Strengths in the response and remediation landscape​

• The maintainer issued a public security advisory and a targeted patch (1.4.3) that addresses both the heap corruption and residual DoS loop issues. This is the right fix: correct the arithmetic and guard conditions at the C level. (github.com)
• Distribution maintainers (Debian, Fedora, etc.) and vendors integrated the fix into packaged updrh standard update channels.

Residual and systemic risks​

• The true exposure is surprisingly brittle: many teams assume 64‑bit deployments and neglect to inventory 32‑bit builds, older containers, or vendorized binaries that still compile extensions for 32‑bit compatibility. These stale artifacts are a real risk until rebuilt.
• Heap corruption bugs are a slippery class: maintainers doin many write‑ups (and that is often accurate), but in specific allocator and environment conditions heap corruption can be escalated. Defenders should not discount that possibility entirely.
• Detection gaps: oversized payloads may be rare in logs and, without explicit size thresholds, may slip through monitoring until a crash reveals the issue. Proactive WAF/body‑size caps are low‑cost mitigations that pay dividends. (github.com)

Lessons for secure engineering​

• Small integer/size mathis an ongoing attack surface. Projects that mix high‑level languages with C extensions should prioritize fuzzing, bounds checks, and explicit size validation.
• Supply‑chain hygiene matters: patching package managers is necessary but not sufficient — static binaries and vendorized extensions require rebuilds. Automated SBOM and rebuild policies reduce this gap.

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Conclusion — what to do now​

• Immediate: identify any yajl‑ruby <= 1.4.2 in your environment, and upgrade to 1.4.3; if that is not immediately possible, enforce body size limits, sandbox parsing, and add rate‑limits/WAF protections. (github.com)
• Medium term: rebuild vendorized or statically compiled artifacts that include native extensions, add CI checks to block vulnerable gem versions, and include yajl‑ruby checks in your SBOM and image scanning pipelines.
• Longer term: adopt defensive parsing practices and isolation patterns for untrusted inputs; integrate fuzz testing and continuous security tooling into native extension workflows to catch integer/alloc issues earlier.

CVE‑2022‑24795 is not a headline‑scale remote takeover vulnerability, but it is a practical, low‑complexity availability risk for any Ruby application that accepts extremely large JSON inputs — and as we know from prior similar vulnerabilities, availability attacks are disruptive, relatively cheap for attackers, and costly for operators. Patch, contain, and verify your builds. (github.com)

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Source: MSRC Security Update Guide - Microsoft Security Response Center