SRE-1054: Bump next and astro past this week's critical advisories

[claude]

Before: hash-frontend and hash-isomorphic-utils are on next 15.5.21, which carries two unauthenticated-RCE advisories: GHSA-2xp9-vwfh-vxw4 (Image Optimization API, AVIF files) and GHSA-p293-qw3h-jr36 (Windows-hosted servers). petrinaut-docs is on astro 7.1.6, which carries a separate critical.

After: next bumped to 15.5.24 (fixes both advisories on the 15.x line) and astro bumped to 7.2.8, both same-major patch/minor bumps.

How: yarn up -R next astro plus yarn dedupe --strategy highest, using the repo's pinned yarn 4.16.0. Verified both vulnerable versions are absent from the lockfile and yarn install --immutable passes.

🤖 Generated with Claude Code

https://claude.ai/code/session_01USoBhopP9ZUAu63qfhxE7D

---

Generated by Claude Code

[vercel]

The latest updates on your projects. Learn more about Vercel for GitHub.

Project	Deployment	Actions	Updated
hash	Ready	Preview	Sep 15, 2026 9:39am UTC
hashdotdesign-tokens	Ready	Preview	Sep 15, 2026 9:39am UTC
petrinaut	Ready	Preview	Sep 15, 2026 9:39am UTC
petrinaut-docs	Ready	Preview	Sep 15, 2026 9:39am UTC

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 66.28%. Comparing base (fb728e4) to head (3464003).
⚠️ Report is 46 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #9701      +/-   ##
==========================================
+ Coverage   65.90%   66.28%   +0.38%     
==========================================
  Files        1887     1775     -112     
  Lines      198443   191861    -6582     
  Branches     8248     7853     -395     
==========================================
- Hits       130774   127173    -3601     
+ Misses      66139    63207    -2932     
+ Partials     1530     1481      -49     

Flag	Coverage Δ
apps.hash-ai-worker-py	?
apps.hash-ai-worker-ts	1.99% <ø> (ø)
apps.hash-api	15.35% <ø> (ø)
backend-integration-tests	?
deer	?
error-stack	?
local.hash-backend-utils	3.27% <ø> (ø)
local.hash-isomorphic-utils	12.22% <ø> (ø)
local.hash-subgraph	?
rust.deer	?
rust.sarif	?
sarif	?
tests.hash-backend-integration	?
unit-tests	?

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[codspeed-hq]

Merging this PR will not alter performance

⚠️ 6 benchmarks measured no execution time

Nothing ran under measurement, usually because the compiler removed the code under test. These results are not comparable, so they count as unchanged.

Preventing compiler optimizations

✅ 98 untouched benchmarks

Performance Changes

	Benchmark	BASE	HEAD	Efficiency
⚠️	as_constant	< 1 ns	< 1 ns	N/A
⚠️	constant_equal	< 1 ns	< 1 ns	N/A
⚠️	constant_not_equal	< 1 ns	< 1 ns	N/A
⚠️	access	< 1 ns	< 1 ns	N/A
⚠️	runtime_equal	< 1 ns	< 1 ns	N/A
⚠️	runtime_not_equal	< 1 ns	< 1 ns	N/A

---

_{Comparing claude/sre-1054-bump-next-astro-critical-rce (3464003) with main (434cedb)¹}

Footnotes

1. No successful run was found on main (466cc6b) during the generation of this report, so 434cedb was used instead as the comparison base. There might be some changes unrelated to this pull request in this report. ↩

[claude]

Fixed in 9f9ef66: the Semgrep PRO finding on sharp 0.35.3 (GHSA-rgj7-g3m4-5g8c, vulnerable bundled libheif) traced back to a stale next/sharp: 0.35.3 resolution already in this repo's package.json — it was still forcing that version into next's own nested node_modules even after next itself no longer required it. Bumped next to 15.5.25 (its own fix for this range) and the resolution + two direct petrinaut-docs/petrinaut-website pins to 0.35.4. Verified with a fresh osv-scanner pass that no sharp finding remains.

[cursor]

PR Summary

Low Risk
Same-major dependency bumps with no application code changes; main regression surface is Next image optimization and Astro docs builds.

Overview
Bumps Next.js from 15.5.21 to 15.5.25 in hash-frontend and hash-isomorphic-utils, addressing recent unauthenticated RCE advisories on the Image Optimization / Windows hosting paths described in the PR.

Bumps Astro from 7.1.6 to 7.2.8 in petrinaut-docs for the related critical advisory on that line. The lockfile refresh also pulls sharp to 0.35.4 (including the root next/sharp resolution and Petrinaut apps) and transitively updates Astro’s compiler/satteri stack—no application source changes, only package.json / yarn.lock.

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[github-actions]

Benchmark results

@rust/hash-graph-benches – Integrations

policy_resolution_large

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2002	$$28.9 \mathrm{ms} \pm 250 \mathrm{μs}\left({\color{gray}4.31 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.49 \mathrm{ms} \pm 25.1 \mathrm{μs}\left({\color{gray}1.15 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 1002	$$13.1 \mathrm{ms} \pm 101 \mathrm{μs}\left({\color{gray}0.469 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 3314	$$43.7 \mathrm{ms} \pm 399 \mathrm{μs}\left({\color{gray}-0.850 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$14.7 \mathrm{ms} \pm 201 \mathrm{μs}\left({\color{gray}2.01 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 1527	$$25.2 \mathrm{ms} \pm 270 \mathrm{μs}\left({\color{gray}1.95 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 2078	$$30.0 \mathrm{ms} \pm 234 \mathrm{μs}\left({\color{gray}4.98 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.81 \mathrm{ms} \pm 24.6 \mathrm{μs}\left({\color{gray}1.35 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 1033	$$14.2 \mathrm{ms} \pm 124 \mathrm{μs}\left({\color{gray}0.963 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_medium

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 102	$$3.85 \mathrm{ms} \pm 23.9 \mathrm{μs}\left({\color{gray}0.185 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$3.03 \mathrm{ms} \pm 17.4 \mathrm{μs}\left({\color{gray}0.288 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 52	$$3.43 \mathrm{ms} \pm 25.6 \mathrm{μs}\left({\color{gray}0.514 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 269	$$5.31 \mathrm{ms} \pm 35.5 \mathrm{μs}\left({\color{gray}1.00 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.62 \mathrm{ms} \pm 24.6 \mathrm{μs}\left({\color{gray}1.33 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 108	$$4.25 \mathrm{ms} \pm 35.2 \mathrm{μs}\left({\color{gray}0.924 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 133	$$4.60 \mathrm{ms} \pm 35.3 \mathrm{μs}\left({\color{gray}1.64 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.48 \mathrm{ms} \pm 23.1 \mathrm{μs}\left({\color{gray}0.395 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 63	$$4.30 \mathrm{ms} \pm 32.5 \mathrm{μs}\left({\color{gray}1.69 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_none

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 2	$$2.75 \mathrm{ms} \pm 23.2 \mathrm{μs}\left({\color{gray}0.025 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.69 \mathrm{ms} \pm 17.8 \mathrm{μs}\left({\color{gray}0.248 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 2	$$2.81 \mathrm{ms} \pm 16.3 \mathrm{μs}\left({\color{gray}-0.662 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 8	$$3.10 \mathrm{ms} \pm 22.5 \mathrm{μs}\left({\color{gray}1.39 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$2.88 \mathrm{ms} \pm 19.2 \mathrm{μs}\left({\color{gray}-0.395 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 3	$$3.18 \mathrm{ms} \pm 19.8 \mathrm{μs}\left({\color{gray}-0.614 \mathrm{\%}}\right) $$	Flame Graph

policy_resolution_small

Function	Value	Mean	Flame graphs
resolve_policies_for_actor	user: empty, selectivity: high, policies: 52	$$3.14 \mathrm{ms} \pm 26.1 \mathrm{μs}\left({\color{gray}0.486 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: low, policies: 1	$$2.79 \mathrm{ms} \pm 16.6 \mathrm{μs}\left({\color{gray}-1.922 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: empty, selectivity: medium, policies: 26	$$3.00 \mathrm{ms} \pm 18.6 \mathrm{μs}\left({\color{gray}-0.113 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: high, policies: 94	$$3.57 \mathrm{ms} \pm 23.8 \mathrm{μs}\left({\color{gray}-0.391 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: low, policies: 1	$$3.08 \mathrm{ms} \pm 24.8 \mathrm{μs}\left({\color{gray}-0.531 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: seeded, selectivity: medium, policies: 27	$$3.32 \mathrm{ms} \pm 20.4 \mathrm{μs}\left({\color{gray}-1.043 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: high, policies: 66	$$3.51 \mathrm{ms} \pm 25.8 \mathrm{μs}\left({\color{gray}-0.260 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: low, policies: 1	$$3.07 \mathrm{ms} \pm 21.3 \mathrm{μs}\left({\color{gray}0.374 \mathrm{\%}}\right) $$	Flame Graph
resolve_policies_for_actor	user: system, selectivity: medium, policies: 29	$$3.42 \mathrm{ms} \pm 26.4 \mathrm{μs}\left({\color{gray}1.26 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_complete

Function	Value	Mean	Flame graphs
entity_by_id;one_depth	1 entities	$$31.7 \mathrm{ms} \pm 188 \mathrm{μs}\left({\color{gray}-0.657 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	10 entities	$$71.6 \mathrm{ms} \pm 452 \mathrm{μs}\left({\color{gray}-0.246 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	25 entities	$$35.1 \mathrm{ms} \pm 198 \mathrm{μs}\left({\color{gray}-1.823 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	5 entities	$$39.7 \mathrm{ms} \pm 304 \mathrm{μs}\left({\color{gray}-1.386 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;one_depth	50 entities	$$41.8 \mathrm{ms} \pm 319 \mathrm{μs}\left({\color{gray}0.944 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	1 entities	$$33.7 \mathrm{ms} \pm 219 \mathrm{μs}\left({\color{gray}0.496 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	10 entities	$$435 \mathrm{ms} \pm 1.37 \mathrm{ms}\left({\color{gray}1.90 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	25 entities	$$92.2 \mathrm{ms} \pm 602 \mathrm{μs}\left({\color{gray}1.83 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	5 entities	$$79.3 \mathrm{ms} \pm 594 \mathrm{μs}\left({\color{gray}0.210 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;two_depth	50 entities	$$277 \mathrm{ms} \pm 949 \mathrm{μs}\left({\color{lightgreen}-8.794 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	1 entities	$$10.4 \mathrm{ms} \pm 55.0 \mathrm{μs}\left({\color{gray}-0.038 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	10 entities	$$10.5 \mathrm{ms} \pm 76.2 \mathrm{μs}\left({\color{gray}-0.586 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	25 entities	$$10.7 \mathrm{ms} \pm 66.4 \mathrm{μs}\left({\color{gray}1.09 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	5 entities	$$10.5 \mathrm{ms} \pm 79.1 \mathrm{μs}\left({\color{gray}-0.340 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id;zero_depth	50 entities	$$10.6 \mathrm{ms} \pm 75.0 \mathrm{μs}\left({\color{gray}-0.189 \mathrm{\%}}\right) $$	Flame Graph

read_scaling_linkless

Function	Value	Mean	Flame graphs
entity_by_id	1 entities	$$10.4 \mathrm{ms} \pm 63.7 \mathrm{μs}\left({\color{gray}0.225 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10 entities	$$10.4 \mathrm{ms} \pm 68.1 \mathrm{μs}\left({\color{gray}0.968 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	100 entities	$$10.4 \mathrm{ms} \pm 65.1 \mathrm{μs}\left({\color{gray}0.100 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	1000 entities	$$10.5 \mathrm{ms} \pm 79.7 \mathrm{μs}\left({\color{gray}0.433 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	10000 entities	$$10.7 \mathrm{ms} \pm 71.3 \mathrm{μs}\left({\color{gray}0.437 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity

Function	Value	Mean	Flame graphs
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/block/v/1	$$11.1 \mathrm{ms} \pm 92.0 \mathrm{μs}\left({\color{gray}-0.248 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/book/v/1	$$10.9 \mathrm{ms} \pm 75.4 \mathrm{μs}\left({\color{gray}0.533 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/building/v/1	$$10.8 \mathrm{ms} \pm 90.0 \mathrm{μs}\left({\color{gray}-0.440 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/organization/v/1	$$10.8 \mathrm{ms} \pm 66.5 \mathrm{μs}\left({\color{gray}0.534 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/page/v/2	$$10.9 \mathrm{ms} \pm 64.0 \mathrm{μs}\left({\color{gray}-0.146 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/person/v/1	$$10.8 \mathrm{ms} \pm 67.4 \mathrm{μs}\left({\color{gray}0.041 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/playlist/v/1	$$11.0 \mathrm{ms} \pm 93.3 \mathrm{μs}\left({\color{gray}0.631 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/song/v/1	$$10.8 \mathrm{ms} \pm 70.1 \mathrm{μs}\left({\color{gray}-0.424 \mathrm{\%}}\right) $$	Flame Graph
entity_by_id	entity type ID: https://blockprotocol.org/@alice/types/entity-type/uk-address/v/1	$$10.9 \mathrm{ms} \pm 70.6 \mathrm{μs}\left({\color{gray}-0.587 \mathrm{\%}}\right) $$	Flame Graph

representative_read_entity_type

Function	Value	Mean	Flame graphs
get_entity_type_by_id	Account ID: bf5a9ef5-dc3b-43cf-a291-6210c0321eba	$$8.10 \mathrm{ms} \pm 58.6 \mathrm{μs}\left({\color{gray}0.930 \mathrm{\%}}\right) $$	Flame Graph

representative_read_multiple_entities

Function	Value	Mean	Flame graphs
entity_by_property	traversal_paths=0	0	$$58.6 \mathrm{ms} \pm 512 \mathrm{μs}\left({\color{gray}2.19 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$110 \mathrm{ms} \pm 888 \mathrm{μs}\left({\color{gray}1.27 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$64.5 \mathrm{ms} \pm 513 \mathrm{μs}\left({\color{gray}1.48 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$73.8 \mathrm{ms} \pm 580 \mathrm{μs}\left({\color{gray}2.59 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$82.6 \mathrm{ms} \pm 627 \mathrm{μs}\left({\color{gray}1.55 \mathrm{\%}}\right) $$
entity_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$89.1 \mathrm{ms} \pm 587 \mathrm{μs}\left({\color{gray}2.12 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=0	0	$$47.0 \mathrm{ms} \pm 427 \mathrm{μs}\left({\color{gray}2.87 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=255	1,resolve_depths=inherit:1;values:255;properties:255;links:127;link_dests:126;type:true	$$75.3 \mathrm{ms} \pm 542 \mathrm{μs}\left({\color{gray}2.24 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:0;link_dests:0;type:false	$$53.5 \mathrm{ms} \pm 408 \mathrm{μs}\left({\color{gray}2.43 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:0;links:1;link_dests:0;type:true	$$61.9 \mathrm{ms} \pm 406 \mathrm{μs}\left({\color{gray}1.21 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:0;properties:2;links:1;link_dests:0;type:true	$$64.0 \mathrm{ms} \pm 449 \mathrm{μs}\left({\color{gray}1.51 \mathrm{\%}}\right) $$
link_by_source_by_property	traversal_paths=2	1,resolve_depths=inherit:0;values:2;properties:2;links:1;link_dests:0;type:true	$$64.6 \mathrm{ms} \pm 529 \mathrm{μs}\left({\color{gray}2.18 \mathrm{\%}}\right) $$

scenarios

Function	Value	Mean	Flame graphs
full_test	query-limited	$$115 \mathrm{ms} \pm 778 \mathrm{μs}\left({\color{gray}-2.115 \mathrm{\%}}\right) $$	Flame Graph
full_test	query-unlimited	$$127 \mathrm{ms} \pm 748 \mathrm{μs}\left({\color{gray}-1.944 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-limited	$$23.4 \mathrm{ms} \pm 146 \mathrm{μs}\left({\color{gray}2.53 \mathrm{\%}}\right) $$	Flame Graph
linked_queries	query-unlimited	$$514 \mathrm{ms} \pm 1.64 \mathrm{ms}\left({\color{gray}1.76 \mathrm{\%}}\right) $$	Flame Graph