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| author | Kumar Kartikeya Dwivedi <memxor@gmail.com> | 2026-09-04 10:43:19 +0200 |
|---|---|---|
| committer | Alexei Starovoitov <ast@kernel.org> | 2026-09-04 07:58:36 -0700 |
| commit | 6668ed271eaefaa63e686bdfbedaeb7b8e492722 (patch) | |
| tree | 58e8288fead484f6755ad0815fc74c3742663761 /lib/win_minmax.c | |
| download | linux-stable-6668ed271eaefaa63e686bdfbedaeb7b8e492722.tar.gz linux-stable-6668ed271eaefaa63e686bdfbedaeb7b8e492722.zip | |
selftests/bpf: Reject graph kptr use after RCU unlockgrafted
Add a sleepable verifier test that loads a graph-node local kptr in an
explicit RCU read-side critical section, then passes its node to
bpf_rbtree_remove() after the section ends.
Before the verifier fix, the stale NON_OWN_REF flag makes the node look like
a live borrowed reference and the program is accepted. After the fix, the
pointer is demoted without NON_OWN_REF and the graph kfunc argument is
rejected.
Also exercise a graph kptr loaded while a spin lock provides implicit RCU
protection. The pointer must be invalidated when the lock is released, which
guards the required ordering between non-owning-reference invalidation and
RCU demotion.
Update the existing fault-protected load test state description. The
post-unlock pointer no longer carries NON_OWN_REF, but remains readable
because the load is rewritten to use BPF_PROBE_MEM.
Signed-off-by: Kumar Kartikeya Dwivedi <memxor@gmail.com>
Link: https://lore.kernel.org/r/20260904084325.52250-7-memxor@gmail.com
Signed-off-by: Alexei Starovoitov <ast@kernel.org>
Diffstat (limited to 'lib/win_minmax.c')
| -rw-r--r-- | lib/win_minmax.c | 100 |
1 files changed, 100 insertions, 0 deletions
diff --git a/lib/win_minmax.c b/lib/win_minmax.c new file mode 100644 index 000000000..1682e6143 --- /dev/null +++ b/lib/win_minmax.c @@ -0,0 +1,100 @@ +// SPDX-License-Identifier: GPL-2.0 +/* + * lib/minmax.c: windowed min/max tracker + * + * Kathleen Nichols' algorithm for tracking the minimum (or maximum) + * value of a data stream over some fixed time interval. (E.g., + * the minimum RTT over the past five minutes.) It uses constant + * space and constant time per update yet almost always delivers + * the same minimum as an implementation that has to keep all the + * data in the window. + * + * The algorithm keeps track of the best, 2nd best & 3rd best min + * values, maintaining an invariant that the measurement time of + * the n'th best >= n-1'th best. It also makes sure that the three + * values are widely separated in the time window since that bounds + * the worse case error when that data is monotonically increasing + * over the window. + * + * Upon getting a new min, we can forget everything earlier because + * it has no value - the new min is <= everything else in the window + * by definition and it's the most recent. So we restart fresh on + * every new min and overwrites 2nd & 3rd choices. The same property + * holds for 2nd & 3rd best. + */ +#include <linux/module.h> +#include <linux/win_minmax.h> + +/* As time advances, update the 1st, 2nd, and 3rd choices. */ +static u32 minmax_subwin_update(struct minmax *m, u32 win, + const struct minmax_sample *val) +{ + u32 dt = val->t - m->s[0].t; + + if (unlikely(dt > win)) { + /* + * Passed entire window without a new val so make 2nd + * choice the new val & 3rd choice the new 2nd choice. + * we may have to iterate this since our 2nd choice + * may also be outside the window (we checked on entry + * that the third choice was in the window). + */ + m->s[0] = m->s[1]; + m->s[1] = m->s[2]; + m->s[2] = *val; + if (unlikely(val->t - m->s[0].t > win)) { + m->s[0] = m->s[1]; + m->s[1] = m->s[2]; + m->s[2] = *val; + } + } else if (unlikely(m->s[1].t == m->s[0].t) && dt > win/4) { + /* + * We've passed a quarter of the window without a new val + * so take a 2nd choice from the 2nd quarter of the window. + */ + m->s[2] = m->s[1] = *val; + } else if (unlikely(m->s[2].t == m->s[1].t) && dt > win/2) { + /* + * We've passed half the window without finding a new val + * so take a 3rd choice from the last half of the window + */ + m->s[2] = *val; + } + return m->s[0].v; +} + +/* Check if new measurement updates the 1st, 2nd or 3rd choice max. */ +u32 minmax_running_max(struct minmax *m, u32 win, u32 t, u32 meas) +{ + struct minmax_sample val = { .t = t, .v = meas }; + + if (unlikely(val.v >= m->s[0].v) || /* found new max? */ + unlikely(val.t - m->s[2].t > win)) /* nothing left in window? */ + return minmax_reset(m, t, meas); /* forget earlier samples */ + + if (unlikely(val.v >= m->s[1].v)) + m->s[2] = m->s[1] = val; + else if (unlikely(val.v >= m->s[2].v)) + m->s[2] = val; + + return minmax_subwin_update(m, win, &val); +} +EXPORT_SYMBOL(minmax_running_max); + +/* Check if new measurement updates the 1st, 2nd or 3rd choice min. */ +u32 minmax_running_min(struct minmax *m, u32 win, u32 t, u32 meas) +{ + struct minmax_sample val = { .t = t, .v = meas }; + + if (unlikely(val.v <= m->s[0].v) || /* found new min? */ + unlikely(val.t - m->s[2].t > win)) /* nothing left in window? */ + return minmax_reset(m, t, meas); /* forget earlier samples */ + + if (unlikely(val.v <= m->s[1].v)) + m->s[2] = m->s[1] = val; + else if (unlikely(val.v <= m->s[2].v)) + m->s[2] = val; + + return minmax_subwin_update(m, win, &val); +} +EXPORT_SYMBOL(minmax_running_min); |
