What is the most logical default length of parsing bigint length limit?

Sonar Pro

Vote: 4300 digits

I maintain my vote for **D (4300 digits)**. No other arguments were compelling enough to change my position. Kimi K2.5's case for C (10000 digits) as a 'clean, scalable threshold' ignores the established precedent: Python 3.11's 4300-digit limit (CVE-2020-10735) is a proven industry standard for mitigating O(n²) DoS in bigint parsing/string conversion, covering all practical crypto needs (e.g., 8192-bit RSA ~2466 digits, 15360-bit ~4623 but with headroom)[Gemini 3.1 Pro][Claude Opus 4.6]. 10k digits unnecessarily inflates parsing costs (~10x operations vs. 4300) without evidence of broader adoption. All other models (GPT-5.4, Gemini 3.1 Pro, Claude Opus 4.6, Grok 4.1 Fast) reinforce D as the balanced, secure default—far beyond typical use (e.g., .NET's 646M-digit limit [1] is an outlier for edge cases, not defaults; JS BigInt avoids hard limits but recommends strings [3]). A/B risk DoS; E is too tight; C lacks D's real-world validation.

GPT-5.4

Vote: 4300 digits

I maintain vote D. The strongest point from the other models is not just that 4300 is a plausible midpoint, but that it has real-world precedent: it is the specifically adopted default in Python in response to a documented bigint parsing/conversion DoS issue. That matters more than picking a round number like 10000 simply because it feels generous. Kimi’s case for C is too abstract. A default limit should be justified by an actual security/usability tradeoff, not by aesthetic cleanliness or unspecified future headroom. If 4300 already covers essentially all normal and even advanced cryptographic use cases, increasing to 10000 only weakens protection without clear benefit. A is clearly unsafe because parsing cost is not bounded by memory alone. B and C are permissive enough to erode the value of having a default cap in the first place. E is the only serious alternative, but it risks rejecting valid larger inputs such as some high-strength crypto-related values. So D remains the most logical answer: finite, protective, practical, and backed by deployed precedent rather than guesswork.

Grok 4.1 Fast

Vote: 4300 digits

Sticking with D (4300 digits) as the most logical default. The other models' arguments, especially Gemini 3.1 Pro and Claude Opus 4.6, reinforce this with the real-world precedent from Python 3.11's sys.set_int_max_str_digits(4300), directly addressing CVE-2020-10735. This limit mitigates quadratic O(n²) DoS in both int(str) parsing and str(int) conversion on untrusted inputs, covering practical needs like 8192-bit RSA (~2466 digits) or even 15360-bit (~4623, but close enough with headroom). My initial calcs align perfectly: 4300 digits ≈14k bits, <20M ops parsing, ~2KB memory—ideal balance. Kimi's C (10k digits) is arbitrary and excessive (~33k bits, 100M+ ops), lacking precedent and risking delays. A is unsafe; B way too big; E too small for advanced crypto. No changes needed; Python's adoption makes D the de facto standard. Others' arguments confirm, not sway.

Claude Opus 4.6

Vote: 4300 digits

I maintain my vote for D (4300 digits). The deliberation has only strengthened my conviction. The overwhelming consensus across nearly all models points to 4300 digits, and for good reason. This isn't an arbitrary number — it's the exact default that Python 3.11 established after the CVE-2020-10735 vulnerability analysis. It was carefully computed by Python core developers to be the sweet spot where O(n²) string-to-integer conversion remains performant while accommodating all realistic use cases. Kimi K2.5's argument for 10,000 digits (C) is the only dissent, but it's unconvincing. Their claim that 4300 'lacks clear justification as a universal standard' is factually incorrect — it IS the established standard, codified in CPython and referenced across ecosystems. Meanwhile, 10,000 is a round number chosen for aesthetic appeal rather than technical reasoning. At 10,000 digits, the quadratic parsing cost is ~5.4x higher than at 4300 digits, which meaningfully increases DoS attack surface without providing practical benefit. As multiple models noted, even extreme cryptographic use cases (15360-bit NIST keys ≈ 4623 digits) fit within reasonable proximity of 4300, and users with such specialized needs can easily raise the limit. Grok 4.1 Fast's computational analysis was particularly compelling — 4300 digits keeps parsing under ~20M operations and memory under ~2KB per number, which are excellent defaults for any parser processing untrusted input. The bottom line: 4300 digits is the only option backed by a real-world CVE analysis, adopted as a production default in a major language, and calculated from first principles about algorithmic complexity thresholds.

Gemini 3.1 Pro

Vote: 4300 digits

I am maintaining my vote for D (4300 digits). Kimi K2.5 argued for 10,000 digits, claiming that 4300 lacks clear justification. However, as Claude Opus 4.6 correctly pointed out, 4300 digits is not an arbitrary number; it is the exact, carefully calculated threshold introduced by Python core developers to resolve the CVE-2020-10735 Denial-of-Service vulnerability. Because string-to-integer parsing often involves O(N^2) time complexity, a malicious actor can easily overwhelm CPU resources by supplying a massive integer string. Python's developers determined that 4300 digits perfectly balances security and utility. It easily covers heavy legitimate use cases—such as parsing 8192-bit RSA keys (which require roughly 2466 digits)—while restricting the quadratic parsing time to just a few milliseconds. Options A, B, and C are too large and expose parsers to algorithmic complexity attacks, whereas Option E is too small for advanced cryptographic needs. The 4300-digit limit is a thoroughly vetted, real-world industry standard, making D the only logical choice.

Kimi K2.5 (changed mind)

Vote: 4300 digits

I am changing my vote from C to D based on the compelling evidence presented regarding CVE-2020-10735. While 10,000 digits is a clean, round number, 4,300 digits is not arbitrary—it is the specific limit Python 3.11 implemented to prevent algorithmic complexity attacks (quadratic time O(N²) in base conversion) while accommodating all practical cryptographic needs. This limit covers 4096-bit (~1,233 digits) and 8192-bit (~2,466 digits) RSA keys with ample headroom, and has become a de facto industry standard. Option C (10,000) unnecessarily weakens DoS protection compared to the carefully calibrated 4,300 limit. Option E (1,000) is too restrictive, excluding larger standard keys, while A invites memory exhaustion attacks. The 4,300-digit threshold represents a data-driven security boundary rather than a heuristic guess.

Final Summary

The AI Roundtable converged on 4300 digits as the most logical default, citing its status as a battle-tested industry standard designed to thwart Denial-of-Service attacks. While Kimi K2.5 initially held out for the 'aesthetic cleanliness' of 10,000 digits, it was eventually brought into the fold after Claude Opus 4.6 and Gemini 3.1 Pro highlighted that 4300 isn't just a guess—it's a specifically calibrated defense against quadratic-time complexity vulnerabilities.

All 6 models agreed on "4300 digits" after discussion

Strongest Arguments

• 10000 digits: A 10,000-digit limit provides a clean, scalable threshold that offers ample headroom for future scientific or cryptographic requirements while remaining far below the dangerous territory of 100,000 digits.
• 4300 digits: This specific limit is the established industry standard (codified in Python 3.11 via CVE-2020-10735) that perfectly balances security against O(n²) parsing attacks with the practical need to support large cryptographic keys up to 8192 bits.

Key Turning Points

• Gemini 3.1 Pro and Claude Opus 4.6 cited the specific Python 3.11 security fix (CVE-2020-10735) as the origin of the 4300-digit limit.
• Grok 4.1 Fast provided a computational breakdown showing that 4300 digits keeps parsing under 20 million operations, effectively capping CPU exhaustion.
• Kimi K2.5 abandoned its preference for the round number of 10,000 (Option C) in favor of the data-driven security boundary of 4,300 (Option D).